The complete roadmap for beginners to data science and machine learning.
About This Video
In Detail
This course is crafted to teach you the most in-demand skills in the real world. This course aims to help you …
The complete roadmap for beginners to data science and machine learning.
About This Video
In Detail
This course is crafted to teach you the most in-demand skills in the real world. This course aims to help you understand all the data science and machine learning concepts and methodologies with regard to Python.
When you take a quick look at the different sections of this course, you may think of these sections as being independent. However, these sections are interlinked and almost sequential. Each section is an independent concept and is like a course on its own. We have deliberately arranged these sections in a sequence as each subsequent section builds upon the sections you have completed. This framework enables you to explore more independent concepts easily.
At the end of every subsection, you are assigned homework to further strengthen your learning. All these assessments are based on the previous concepts and methods you have learned. Several of these assessment tasks will be coding-based, as the main aim is to get you up and proceeding to implementations.
By the end of this course, you will be able to easily tackle real-world problems and ensure steady career growth and will be equipped with the knowledge of all the essential concepts you need to excel as a data science professional.
Who this book is for
This course is designed for people who want to become perfect in their data speak; people who want to learn data science and machine learning with real datasets in data science; people from a non-engineering background who want to enter the data science field; people who want to enter the machine learning field; people who want to learn data science and machine learning along with its implementation in realistic projects.
For this course, no prior knowledge is needed. You will start with the basic concepts and gradually build your knowledge of the subject.
Chapter 1 : Introduction to the Course
Introduction to Courses and Instructor
Chapter 2 : Basics for Data Science: Python for Data Science and Data Analysis
Introduction - Part 1
Introduction - Part 2
Basics of Programming: Understanding the Algorithm
Basics of Programming: FlowCharts and Pseudocodes
Basics of Programming: Example of Algorithms - Making Tea Problem
Basics of Programming: Example of Algorithms-Searching Minimum
Basics of Programming: Example of Algorithms-Sorting Problem
Basics of Programming: Sorting Problem in Python
Why Python and Jupyter Notebook: Why Python
Why Python and Jupyter Notebook: Why Jupyter Notebooks
Installation of Anaconda and IPython Shell: Installing Python and Jupyter Anaconda
Installation of Anaconda and IPython Shell: Your First Python Code - Hello World
Installation of Anaconda and IPython Shell: Coding in IPython Shell
Variable and Operator: Variables
Variable and Operator: Operators
Variable and Operator: Variable Name Quiz
Variable and Operator: Bool Data Type in Python
Variable and Operator: Comparison in Python
Variable and Operator: Combining Comparisons in Python
Variable and Operator: Combining Comparisons Quiz
Python Useful function: Python Function- Round
Python Useful function: Python Function- Divmod
Python Useful function: Python Function- Is instance and PowFunctions
Python Useful function: Python Function- Input
Control Flow in Python: If Python Condition
Control Flow in Python: if Elif Else Python Conditions
Control Flow in Python: More on if Elif Else Python Conditions
Control Flow in Python: Indentations
Control Flow in Python: Comments and Problem-Solving Practice with If
Control Flow in Python: While Loop
Control Flow in Python: While Loop Break Continue
Control Flow in Python: For Loop
Control Flow in Python: Else in For Loop
Control Flow in Python: Loops Practice-Sorting Problem
Function and Module in Python: Functions in Python
Function and Module in Python: DocString
Function and Module in Python: Input Arguments
Function and Module in Python: Multiple Input Arguments
Function and Module in Python: Ordering Multiple Input Arguments
Function and Module in Python: Output Arguments and Return Statement
Function and Module in Python: Function Practice-Output Arguments and Return Statement
Function and Module in Python: Variable Number of Input Arguments
Function and Module in Python: Variable Number of Input Arguments as Dictionary
Function and Module in Python: Default Values in Python
Function and Module in Python: Modules in Python
Function and Module in Python: Making Modules in Python
Function and Module in Python: Function Practice-Sorting List in Python
String in Python: Strings
String in Python: Multi-Line Strings
String in Python: Indexing Strings
String in Python: String Methods
String in Python: String Escape Sequences
Data Structure (List, Tuple, Set, Dictionary): Introduction to Data Structure
Data Structure (List, Tuple, Set, Dictionary): Defining and Indexing
Data Structure (List, Tuple, Set, Dictionary): Insertion and Deletion
Data Structure (List, Tuple, Set, Dictionary): Python Practice-Insertion and Deletion
Data Structure (List, Tuple, Set, Dictionary): Deep Copy or Reference Slicing
Data Structure (List, Tuple, Set, Dictionary): Exploring Methods Using TAB Completion
Data Structure (List, Tuple, Set, Dictionary): Data Structure Abstract Ways
Data Structure (List, Tuple, Set, Dictionary): Data Structure Practice
NumPy for Numerical Data Processing: Introduction to NumPy
NumPy for Numerical Data Processing: NumPy Dimensions
NumPy for Numerical Data Processing: NumPy Shape, Size, and Bytes
NumPy for Numerical Data Processing: Arrange, Random, and Reshape-Part 1
NumPy for Numerical Data Processing: Arrange, Random, and Reshape-Part 2
NumPy for Numerical Data Processing: Slicing-Part 1
NumPy for Numerical Data Processing: Slicing-Part 2
NumPy for Numerical Data Processing: NumPy Masking
NumPy for Numerical Data Processing: NumPy BroadCasting and Concatenation
NumPy for Numerical Data Processing: NumPy ufuncs Speed Test
Pandas for Data Manipulation: Introduction to Pandas
Pandas for Data Manipulation: Pandas Series
Pandas for Data Manipulation: Pandas Data Frame
Pandas for Data Manipulation: Pandas Missing Values
Pandas for Data Manipulation: Pandas .loc and .iloc
Pandas for Data Manipulation: Pandas Practice-Using COVID19 Data - Part 1
Pandas for Data Manipulation: Pandas Practice-Using COVID19 Data - Part 2
Matplotlib, Seaborn, and Bokeh for Data Visualization: Introduction to Matplotlib
Matplotlib, Seaborn, and Bokeh for Data Visualization: Seaborn Versus Matplotlib Style
Matplotlib, Seaborn, and Bokeh for Data Visualization: Histograms Kdeplot
Matplotlib, Seaborn, and Bokeh for Data Visualization: Seaborn Pairplot and Jointplot
Matplotlib, Seaborn, and Bokeh for Data Visualization: Seaborn Pairplot using Iris Data
Matplotlib, Seaborn, and Bokeh for Data Visualization: Introduction to Bokeh
Matplotlib, Seaborn, and Bokeh for Data Visualization: Bokeh Gridplot
Scikit-Learn for Machine Learning: Introduction to Scikit-Learn
Scikit-Learn for Machine Learning: Scikit-Learn for Linear Regression
Scikit-Learn for Machine Learning: Scikit-Learn for SVM and Random Forests
Scikit-Learn for Machine Learning: Scikit-Learn - Trend Analysis COVID19
Chapter 3 : Basics for Data Science: Data Understanding and Data Visualization with Python
Introduction
What We will Learn
NumPy for Numerical Data Processing: Ufuncs Add, Sum, and Plus Operators
NumPy for Numerical Data Processing: Ufuncs Subtract Power Mod
NumPy for Numerical Data Processing: Ufuncs Comparisons Logical Operators
NumPy for Numerical Data Processing: Ufuncs Comparisons Logical Operators Quiz
NumPy for Numerical Data Processing: Ufuncs Comparisons Logical Operators Solution
NumPy for Numerical Data Processing: Ufuncs Output Argument
NumPy for Numerical Data Processing: NumPy Playing with Images
NumPy for Numerical Data Processing: NumPy Playing with Images Quiz
NumPy for Numerical Data Processing: NumPy Playing with Images Solution
NumPy for Numerical Data Processing: NumPy KNN Classifier from Scratch
NumPy for Numerical Data Processing: NumPy Structured Arrays
NumPy for Numerical Data Processing: NumPy Structured Arrays Quiz
NumPy for Numerical Data Processing: NumPy Structured Arrays Solution
Pandas for Data Manipulation and Understanding: Introduction to Pandas
Pandas for Data Manipulation and Understanding: Pandas Series
Pandas for Data Manipulation and Understanding: Pandas DataFrame
Pandas for Data Manipulation and Understanding: Pandas DataFrame Quiz
Pandas for Data Manipulation and Understanding: Pandas DataFrame Solution
Pandas for Data Manipulation and Understanding: Pandas Missing Values
Pandas for Data Manipulation and Understanding: Pandas Loc Iloc
Pandas for Data Manipulation and Understanding: Pandas in Practice
Pandas for Data Manipulation and Understanding: Pandas Group By
Pandas for Data Manipulation and Understanding: Pandas Group By Quiz
Pandas for Data Manipulation and Understanding: Pandas Group by Solution
Pandas for Data Manipulation and Understanding: Hierarchical Indexing
Pandas for Data Manipulation and Understanding: Pandas Rolling
Pandas for Data Manipulation and Understanding: Pandas Rolling Quiz
Pandas for Data Manipulation and Understanding: Pandas Rolling Solution
Pandas for Data Manipulation and Understanding: Pandas Where
Pandas for Data Manipulation and Understanding: Pandas Clip
Pandas for Data Manipulation and Understanding: Pandas Clip Quiz
Pandas for Data Manipulation and Understanding: Pandas Clip Solution
Pandas for Data Manipulation and Understanding: Pandas Merge
Pandas for Data Manipulation and Understanding: Pandas Merge Quiz
Pandas for Data Manipulation and Understanding: Pandas Merge Solution
Pandas for Data Manipulation and Understanding: Pandas Pivot Table
Pandas for Data Manipulation and Understanding: Pandas Strings
Pandas for Data Manipulation and Understanding: Pandas DateTime
Pandas for Data Manipulation and Understanding: Pandas Hands on COVID19 Data
Pandas for Data Manipulation and Understanding: Pandas Hands on COVID19 Data Bug
Matplotlib for Data Visualization: Introduction to Matplotlib
Matplotlib for Data Visualization: Matplotlib Multiple Plots
Matplotlib for Data Visualization: Matplotlib Colors and Styles
Matplotlib for Data Visualization: Matplotlib Colors and Styles Quiz
Matplotlib for Data Visualization: Matplotlib Colors and Styles Solution
Matplotlib for Data Visualization: Matplotlib Colors and Styles Shortcuts
Matplotlib for Data Visualization: Matplotlib Axis Limits
Matplotlib for Data Visualization: Matplotlib Axis Limits Quiz
Matplotlib for Data Visualization: Matplotlib Axis Limits Solution
Matplotlib for Data Visualization: Matplotlib Legends Labels
Matplotlib for Data Visualization: Matplotlib Set Function
Matplotlib for Data Visualization: Matplotlib Set Function Quiz
Matplotlib for Data Visualization: Matplotlib Set Function Solution
Matplotlib for Data Visualization: Matplotlib Markers
Matplotlib for Data Visualization: Matplotlib Markers Randomplots
Matplotlib for Data Visualization: Matplotlib Scatter Plot
Matplotlib for Data Visualization: Matplotlib Contour Plot
Matplotlib for Data Visualization: Matplotlib Contour Plot Quiz
Matplotlib for Data Visualization: Matplotlib Contour Plot Solution
Matplotlib for Data Visualization: Matplotlib Histograms
Matplotlib for Data Visualization: Matplotlib Subplots
Matplotlib for Data Visualization: Matplotlib Subplots Quiz
Matplotlib for Data Visualization: Matplotlib Subplots Solution
Matplotlib for Data Visualization: Matplotlib 3D Introduction
Matplotlib for Data Visualization: Matplotlib 3D Scatter Plots
Matplotlib for Data Visualization: Matplotlib 3D Scatter Plots Quiz
Matplotlib for Data Visualization: Matplotlib 3D Scatter Plots Solution
Matplotlib for Data Visualization: Matplotlib 3D Surface Plots
Seaborn for Data Visualization: Introduction to Seaborn
Seaborn for Data Visualization: Seaborn Relplot
Seaborn for Data Visualization: Seaborn Relplot Quiz
Seaborn for Data Visualization: Seaborn Relplot Solution
Seaborn for Data Visualization: Seaborn Relplot Kind Line
Seaborn for Data Visualization: Seaborn Relplot Facets
Seaborn for Data Visualization: Seaborn Relplot Facets Quiz
Seaborn for Data Visualization: Seaborn Relplot Facets Solution
Seaborn for Data Visualization: Seaborn Catplot
Seaborn for Data Visualization: Seaborn Heatmaps
Bokeh for Interactive Plotting: Introduction to Bokeh
Bokeh for Interactive Plotting: Bokeh Multiplots Markers
Bokeh for Interactive Plotting: Bokeh Multiplots Grid Plot
Bokeh for Interactive Plotting: Bokeh Multiplots Grid Plot Quiz
Bokeh for Interactive Plotting: Bokeh Multiplots Grid Plot Solution
Plotly for 3D Interactive Plotting: Plotly 3D Interactive Scatter Plot
Plotly for 3D Interactive Plotting: Plotly 3D Interactive Scatter Plot Quiz
Plotly for 3D Interactive Plotting: Plotly 3D Interactive Scatter Plot Solution
Plotly for 3D Interactive Plotting: Plotly 3D Interactive Surface Plot
Plotly for 3D Interactive Plotting: Plotly 3D Interactive Surface Plot Quiz
Plotly for 3D Interactive Plotting: Plotly 3D Interactive Surface Plot Solution
Geographic Maps with Folium: Geographic Maps with Folium using COVID-19 Data
Geographic Maps with Folium: Geographic Maps with Folium using COVID-19 Data Quiz
Geographic Maps with Folium: Geographic Maps with Folium using COVID-19 Data Solution
Pandas for Plotting: Pandas for Plotting
Chapter 4 : Basics for Data Science: Mastering Probability and Statistics in Python
Introduction
Probability Versus Statistics
Sets: Definition of Set
Sets: Definition of Set Exercise 01
Sets: Definition of Set Solution 01
Sets: Definition of Set Exercise 02
Sets: Definition of Set Solution 02
Sets: Cardinality of a Set
Sets: Subsets PowerSet UniversalSet
Sets: Python Practice Subsets
Sets: PowerSets Solution
Sets: Operations
Sets: Operations Exercise 01
Sets: Operations Solution 01
Sets: Operations Exercise 02
Sets: Operations Solution 02
Sets: Operations Exercise 03
Sets: Operations Solution 03
Sets: Python Practice Operations
Sets: Venn Diagrams Operations
Sets: Homework
Experiment: Random Experiment
Experiment: Outcome and Sample Space
Experiment: Outcome and Sample Space Exercise 01
Experiment: Outcome and Sample Space Solution 01
Experiment: Event
Experiment: Event Exercise 01
Experiment: Event Solution 01
Experiment: Event Exercise 02
Experiment: Event Solution 02
Experiment: Recap and Homework
Probability Model: Probability Model
Probability Model: Probability Axioms
Probability Model: Probability Axioms Derivations
Probability Model: Probability Axioms Derivations Exercise 01
Probability Model: Probability Axioms Derivations Solution 01
Probability Model: Probability Models Example
Probability Model: Probability Models More Examples
Probability Model: Probability Models Continuous
Probability Model: Conditional Probability
Probability Model: Conditional Probability Example
Probability Model: Conditional Probability Formula
Probability Model: Conditional Probability in Machine Learning
Probability Model: Conditional Probability Total Probability Theorem
Probability Model: Probability Models Independence
Probability Model: Probability Models Conditional Independence
Probability Model: Probability Models Conditional Independence Exercise 01
Probability Model: Probability Models Conditional Independence Solution 01
Probability Model: Probability Models BayesRule
Probability Model: Probability Models towards Random Variables
Probability Model: Homework
Random Variables: Introduction
Random Variables: Random Variables Examples
Random Variables: Random Variables Examples Exercise 01
Random Variables: Random Variables Examples Solution 01
Random Variables: Bernulli Random Variables
Random Variables: Bernulli Trail Python Practice
Random Variables: Bernulli Trail Python Practice Exercise 01
Random Variables: Bernulli Trail Python Practice Solution 01
Random Variables: Geometric Random Variable
Random Variables: Geometric Random Variable Normalization Proof Optional
Random Variables: Geometric Random Variable Python Practice
Random Variables: Binomial Random Variables
Random Variables: Binomial Python Practice
Random Variables: Random Variables in Real Datasets
Random Variables: Random Variables in Real Datasets Exercise 01
Random Variables: Random Variables in Real Datasets Solution 01
Random Variables: Homework
Continuous Random Variables: Zero Probability to Individual Values
Continuous Random Variables: Zero Probability to Individual Values Exercise 01
Continuous Random Variables: Zero Probability to Individual Values Solution 01
Continuous Random Variables: Probability Density Functions
Continuous Random Variables: Probability Density Functions Exercise 01
Continuous Random Variables: Probability Density Functions Solution 01
Continuous Random Variables: Uniform Distribution
Continuous Random Variables: Uniform Distribution Exercise 01
Continuous Random Variables: Uniform Distribution Solution 01
Continuous Random Variables: Uniform Distribution Python
Continuous Random Variables: Exponential
Continuous Random Variables: Exponential Exercise 01
Continuous Random Variables: Exponential Solution 01
Continuous Random Variables: Exponential Python
Continuous Random Variables: Gaussian Random Variables
Continuous Random Variables: Gaussian Random Variables Exercise 01
Continuous Random Variables: Gaussian Random Variables Solution 01
Continuous Random Variables: Gaussian Python
Continuous Random Variables: Transformation of Random Variables
Continuous Random Variables: Homework
Expectations: Definition
Expectations: Sample Mean
Expectations: Law of Large Numbers
Expectations: Law of Large Numbers Famous Distributions
Expectations: Law of Large Numbers Famous Distributions Python
Expectations: Variance
Expectations: Homework
Project Bayes Classifier: Project Bayes Classifier from Scratch
Multiple Random Variables: Joint Distributions
Multiple Random Variables: Joint Distributions Exercise 01
Multiple Random Variables: Joint Distributions Solution 01
Multiple Random Variables: Joint Distributions Exercise 02
Multiple Random Variables: Joint Distributions Solution 02
Multiple Random Variables: Joint Distributions Exercise 03
Multiple Random Variables: Joint Distributions Solution 03
Multiple Random Variables: Multivariate Gaussian
Multiple Random Variables: Conditioning Independence
Multiple Random Variables: Classification
Multiple Random Variables: Naive Bayes Classification
Multiple Random Variables: Regression
Multiple Random Variables: Curse of Dimensionality
Multiple Random Variables: Homework
Optional Estimation: Parametric Distributions
Optional Estimation: MLE
Optional Estimation: Loglikelihood
Optional Estimation: MAP
Optional Estimation: Logistic Regression
Optional Estimation: Ridge Regression
Optional Estimation: DNN
Mathematical Derivations for Math Lovers (Optional): Permutations
Mathematical Derivations for Math Lovers (Optional): Combinations
Mathematical Derivations for Math Lovers (Optional): Binomial Random Variable
Mathematical Derivations for Math Lovers (Optional): Logistic Regression Formulation
Mathematical Derivations for Math Lovers (Optional): Logistic Regression Derivation
Chapter 5 : Machine Learning: Machine Learning Crash Course
Introduction
Introduction: Python Practical of the Course
Why Machine Learning: Machine Learning Applications-Part 1
Why Machine Learning: Machine Learning Applications-Part 2
Why Machine Learning: Why Machine Learning is Trending Now
Process of Learning from Data: Supervised Learning
Process of Learning from Data: Unsupervised Learning and Reinforcement Learning
Machine Learning Methods: Features
Machine Learning Methods: Features Practice with Python
Machine Learning Methods: Regression
Machine Learning Methods: Regression Practice with Python
Machine Learning Methods: Classification
Machine Learning Methods: Classification Practice with Python
Machine Learning Methods: Clustering
Machine Learning Methods: Clustering Practice with Python
Data Preparation and Pre-processing: Handling Image Data
Data Preparation and Preprocessing: Handling Video and Audio Data
Data Preparation and Preprocessing: Handling Text Data
Data Preparation and Preprocessing: One Hot Encoding
Data Preparation and Preprocessing: Data Standardization
Machine Learning Models and Optimization: Machine Learning Model 1
Machine Learning Models and Optimization: Machine Learning Model 2
Machine Learning Models and Optimization: Machine Learning Model 3
Machine Learning Models and Optimization: Training Process, Error, Cost and Loss
Machine Learning Models and Optimization: Optimization
Building Machine Learning Model from Scratch: Linear Regression from Scratch- Part 1
Building Machine Learning Model from Scratch: Linear Regression from Scratch- Part 2
Building Machine Learning Model from Scratch: Minimum-to-mean Distance Classifier from Scratch- Part 1
Building Machine Learning Model from Scratch: Minimum-to-mean Distance Classifier from Scratch- Part 2
Building Machine Learning Model from Scratch: K-Means Clustering from Scratch- Part 1
Building Machine Learning Model from Scratch: K-Means Clustering from Scratch- Part 2
Overfitting, Underfitting, and Generalization: Overfitting Introduction
Overfitting, Underfitting, and Generalization: Overfitting Example in Python
Overfitting, Underfitting, and Generalization: Regularization
Overfitting, Underfitting, and Generalization: Generalization
Overfitting, Underfitting, and Generalization: Data Snooping and the Test Set
Overfitting, Underfitting and Generalization: Cross-validation
Machine Learning Model Performance Metrics: The Accuracy
Machine Learning Model Performance Metrics: The Confusion Matrix
Dimensionality Reduction: The Curse of Dimensionality
Dimensionality Reduction: The Principal Component Analysis (PCA)
Deep Learning Overview: Introduction to Deep Neural Networks (DNN)
Deep Learning Overview: Introduction to Convolutional Neural Networks (CNN)
Deep Learning Overview: Introduction to Recurrent Neural Networks (CNN)
Hands-on Machine Learning Project Using Scikit-Learn: Principal Component Analysis (PCA) with Python
Hands-on Machine Learning Project Using Scikit-Learn: Pipeline in Scikit-Learn for Machine Learning Project
Hands-on Machine Learning Project Using Scikit-Learn: Cross-validation with Python
Hands-on Machine Learning Project Using Scikit-Learn: Face Recognition Project with Python
OPTIONAL Section- Mathematics Wrap-Up: Mathematical Wrap-Up on Machine Learning
Chapter 6 : Machine Learning: Feature Engineering and Dimensionality Reduction with Python
Introduction
Features in Data Science: Introduction to Feature in Data Science
Features in Data Science: Marking Facial Features
Features in Data Science: Feature Space
Features in Data Science: Features Dimensions
Features in Data Science: Features Dimensions Activity
Features in Data Science: Why Dimensionality Reduction
Features in Data Science: Activity-Dimensionality Reduction
Features in Data Science: Feature Dimensionality Reduction Methods
Feature Selection: Why Feature Selection
Feature Selection: Feature Selection Methods
Feature Selection: Filter Methods
Feature Selection: Wrapper Methods
Feature Selection: Embedded Methods
Feature Selection: Search Strategy
Feature Selection: Search Strategy Activity
Feature Selection: Statistical Based Methods
Feature Selection: Information Theoretic Methods
Feature Selection: Similarity Based Methods Introduction
Feature Selection: Similarity Based Methods Criteria
Feature Selection: Activity- Feature Selection in Python
Feature Selection: Activity- Feature Selection
Mathematical Foundation: Introduction to Mathematical Foundation of Feature Selection
Mathematical Foundation: Closure of a Set
Mathematical Foundation: Linear Combinations
Mathematical Foundation: Linear Independence
Mathematical Foundation: Vector Space
Mathematical Foundation: Basis and Dimensions
Mathematical Foundation: Coordinates Versus Dimensions
Mathematical Foundation: SubSpace
Mathematical Foundation: Orthonormal Basis
Mathematical Foundation: Matrix Product
Mathematical Foundation: Least Squares
Mathematical Foundation: Rank
Mathematical Foundation: Eigen Space
Mathematical Foundation: Positive Semi Definite Matrix
Mathematical Foundation: Singular Value Decomposition (SVD)
Mathematical Foundation: Lagrange Multipliers
Mathematical Foundation: Vector Derivatives
Mathematical Foundation: Linear Algebra Module Python
Mathematical Foundation: Activity-Linear Algebra Module Python
Feature Extraction: Feature Extraction Introduction
Feature Extraction: PCA Introduction
Feature Extraction: PCA Criteria
Feature Extraction: PCA Properties
Feature Extraction: PCA Max Variance Formulation
Feature Extraction: PCA Derivation
Feature Extraction: PCA Implementation
Feature Extraction: PCA For Small Sample Size Problems(DualPCA)
Feature Extraction: PCA Versus SVD
Feature Extraction: Kernel PCA
Feature Extraction: Kernel PCA Versus ISOMAP
Feature Extraction: Kernel PCA Versus the Rest
Feature Extraction: Encoder Decoder Networks for Dimensionality Reduction Versus Kernel PCA
Feature Extraction: Supervised PCA and Fishers Linear Discriminant Analysis
Feature Extraction: Supervised PCA and Fishers Linear Discriminant Analysis Activity
Feature Extraction: Dimensionality Reduction Pipelines Python Project
Feature Engineering: Categorical Features
Feature Engineering: Categorical Features Python
Feature Engineering: Text Features
Feature Engineering: Image Features
Feature Engineering: Derived Features
Feature Engineering: Derived Features Histogram of Gradients Local Binary Patterns
Feature Engineering: Feature Scaling
Feature Engineering: Activity-Feature Scaling
Chapter 7 : Deep learning: Artificial Neural Networks with Python
Introduction
Introduction to Machine Learning: Introduction to Machine Learning
Introduction to Machine Learning: Classification
Introduction to Machine Learning: Classification Exercise
Introduction to Machine Learning: Classification Solution
Introduction to Machine Learning: Classification Training Process and Prediction Probabilities
Introduction to Machine Learning: Classification Prediction Probabilities Exercise
Introduction to Machine Learning: Classification Prediction Probabilities Exercise Solution
Introduction to Machine Learning: Regression
Introduction to Machine Learning: Regression Exercise
Introduction to Machine Learning: Regression Exercise Solution
Introduction to Machine Learning: Supervised Learning
Introduction to Machine Learning: Unsupervised Learning
Introduction to Machine Learning: Reinforcement Learning
Introduction to Machine Learning: Machine Learning Model
Introduction to Machine Learning: Machine Learning Model Example
Introduction to Machine Learning: Machine Learning Model Exercise
Introduction to Machine Learning: Machine Learning Model Exercise Solution
Introduction to Machine Learning: Machine Learning Model Types
Introduction to Machine Learning: Machine Learning Model Linearity
Introduction to Machine Learning: Machine Learning Model Linearity Exercise
Introduction to Machine Learning: Machine Learning Model Linearity Exercise Solution
Introduction to Machine Learning: Machine Learning Model Multi Target Models
Introduction to Machine Learning: Machine Learning Model Multi Target Models Exercise
Introduction to Machine Learning: Machine Learning Model Multi Target Models Exercise Solution
Introduction to Machine Learning: Machine Learning Model Training Exercise
Introduction to Machine Learning: Machine Learning Model Training Exercise Solution
Introduction to Machine Learning: Machine Learning Model Training Loss
Introduction to Machine Learning: Machine Learning Model Hyperparameters Exercise
Introduction to Machine Learning: Machine Learning Model Hyperparameters Exercise Solution
Introduction to Machine Learning: Machine Learning Occam’s Razor
Introduction to Machine Learning: Machine Learning Overfitting
Introduction to Machine Learning: Machine Learning Overfitting Exercise
Introduction to Machine Learning: Machine Learning Overfitting Exercise Solution Regularization
Introduction to Machine Learning: Machine Learning Overfitting Generalization
Introduction to Machine Learning: Machine Learning Data Snooping
Introduction to Machine Learning: Machine Learning Cross Validation
Introduction to Machine Learning: Machine Learning Hyperparameter Tunning Exercise
Introduction to Machine Learning: Machine Learning Hyperparameter Tunning Exercise Solution
DNN and Deep Learning Basics: Why PyTorch
DNN and Deep Learning Basics: PyTorch Installation and Tensors Introduction
DNN and Deep Learning Basics: Automatic Differentiation PyTorch New
DNN and Deep Learning Basics: Why DNNs in Machine Learning
DNN and Deep Learning Basics: Representational Power and Data Utilization Capacity of DNN
DNN and Deep Learning Basics: Perceptron
DNN and Deep Learning Basics: Perceptron Exercise
DNN and Deep Learning Basics: Perceptron Exercise Solution
DNN and Deep Learning Basics: Perceptron Implementation
DNN and Deep Learning Basics: DNN Architecture
DNN and Deep Learning Basics: DNN Architecture Exercise
DNN and Deep Learning Basics: DNN Architecture Exercise Solution
DNN and Deep Learning Basics: DNN ForwardStep Implementation
DNN and Deep Learning Basics: DNN Why Activation Function Is Required
DNN and Deep Learning Basics: DNN Why Activation Function Is Required Exercise
DNN and Deep Learning Basics: DNN Why Activation Function Is Required Exercise Solution
DNN and Deep Learning Basics: DNN Properties of Activation Function
DNN and Deep Learning Basics: DNN Activation Functions in PyTorch
DNN and Deep Learning Basics: DNN What is Loss Function
DNN and Deep Learning Basics: DNN What is Loss Function Exercise
DNN and Deep Learning Basics: DNN What is Loss Function Exercise Solution
DNN and Deep Learning Basics: DNN What is Loss Function Exercise 02
DNN and Deep Learning Basics: DNN What is Loss Function Exercise 02 Solution
DNN and Deep Learning Basics: DNN Loss Function in PyTorch
DNN and Deep Learning Basics: DNN Gradient Descent
DNN and Deep Learning Basics: DNN Gradient Descent Exercise
DNN and Deep Learning Basics: DNN Gradient Descent Exercise Solution
DNN and Deep Learning Basics: DNN Gradient Descent Implementation
DNN and Deep Learning Basics: DNN Gradient Descent Stochastic Batch Minibatch
DNN and Deep Learning Basics: DNN Gradient Descent Summary
DNN and Deep Learning Basics: DNN Implementation Gradient Step
DNN and Deep Learning Basics: DNN Implementation Stochastic Gradient Descent
DNN and Deep Learning Basics: DNN Implementation Batch Gradient Descent
DNN and Deep Learning Basics: DNN Implementation Minibatch Gradient Descent
DNN and Deep Learning Basics: DNN Implementation in PyTorch
DNN and Deep Learning Basics: DNN Weights Initializations
DNN and Deep Learning Basics: DNN Learning Rate
DNN and Deep Learning Basics: DNN Batch Normalization
DNN and Deep Learning Basics: DNN Batch Normalization Implementation
DNN and Deep Learning Basics: DNN Optimizations
DNN and Deep Learning Basics: DNN Dropout
DNN and Deep Learning Basics: DNN Dropout in PyTorch
DNN and Deep Learning Basics: DNN Early Stopping
DNN and Deep Learning Basics: DNN Hyperparameters
DNN and Deep Learning Basics: DNN PyTorch CIFAR10 Example
Deep Neural Networks and Deep Learning Basics: Introduction to Artificial Neural Networks
Deep Neural Networks and Deep Learning Basics: Neuron and Perceptron
Deep Neural Networks and Deep Learning Basics: Deep Neural Network Architecture
Deep Neural Networks and Deep Learning Basics: Feedforward Fully Connected MLP
Deep Neural Networks and Deep Learning Basics: Calculating Number of Weights of DNN
Deep Neural Networks and Deep Learning Basics: Number of Neurons Versus Number of Layers
Deep Neural Networks and Deep Learning Basics: Discriminative Versus Generative Learning
Deep Neural Networks and Deep Learning Basics: Universal Approximation Theorem
Deep Neural Networks and Deep Learning Basics: Why Depth
Deep Neural Networks and Deep Learning Basics: Decision Boundary in DNN
Deep Neural Networks and Deep Learning Basics: Bias Term
Deep Neural Networks and Deep Learning Basics: The Activation Function
Deep Neural Networks and Deep Learning Basics: DNN Training Parameters
Deep Neural Networks and Deep Learning Basics: Gradient Descent
Deep Neural Networks and Deep Learning Basics: Backpropagation
Deep Neural Networks and Deep Learning Basics: Training DNN Animation
Deep Neural Networks and Deep Learning Basics: Weight Initialization
Deep Neural Networks and Deep Learning Basics: Batch Minibatch Stochastic
Deep Neural Networks and Deep Learning Basics: Batch Normalization
Deep Neural Networks and Deep Learning Basics: Rprop Momentum
Deep Neural Networks and Deep Learning Basics: convergence Animation
Deep Neural Networks and Deep Learning Basics: Drop Out Early Stopping Hyperparameters
Python for Data Science: Python Packages for Data Science
Python for Data Science: NumPy Pandas and Matplotlib (Part 1)
Python for Data Science: NumPy Pandas and Matplotlib (Part 2)
Python for Data Science: NumPy Pandas and Matplotlib (Part 3)
Python for Data Science: NumPy Pandas and Matplotlib (Part 4)
Python for Data Science: NumPy Pandas and Matplotlib (Part 5)
Python for Data Science: NumPy Pandas and Matplotlib (Part 6)
Python for Data Science: Dataset Preprocessing
Python for Data Science: TensorFlow for classification
Implementation of DNN for COVID 19 Analysis: COVID19 Data Analysis
Implementation of DNN for COVID 19 Analysis: COVID19 Regression with TensorFlow
Chapter 8 : Deep learning: Convolutional Neural Networks with Python
Introduction: Why CNN
Introduction: Focus of the Course
Image Processing: Grayscale Images
Image Processing: RGB Images
Image Processing: Reading and Showing Images in Python
Image Processing: Converting an Image to Grayscale in Python
Image Processing: Image Formation
Image Processing: Image Blurring 1
Image Processing: Image Blurring 2
Image Processing: General Image Filtering
Image Processing: Convolution
Image Processing: Edge Detection
Image Processing: Image Sharpening
Image Processing: Implementation of Image Blurring Edge Detection Image Sharpening in Python
Image Processing: Parametric Shape Detection
Image Processing: Image Processing Activity
Object Detection: Introduction to Object Detection
Object Detection: Classification Pipeline
Object Detection: Sliding Window Implementation
Object Detection: Shift Scale Rotation Invariance
Object Detection: Person Detection
Object Detection: HOG Features
Object Detection: Hand Engineering Versus CNNs
Object Detection: Object Detection Activity
Deep Neural Network Architecture: Convolution Revisited
Deep Neural Network Architecture: Implementing Convolution in Python Revisited
Deep Neural Network Architecture: Why Convolution
Deep Neural Network Architecture: Filters Padding Strides
Deep Neural Network Architecture: Pooling Tensors
Deep Neural Network Architecture: CNN Example
Deep Neural Network Architecture: Convolution and Pooling Details
Deep Neural Network Architecture: Nonvectorized Implementations of Conv2d and Pool2d
Deep Neural Network Architecture Activity
Gradient Descent in CNNs: Example Setup
Gradient Descent in CNNs: Why Derivatives
Gradient Descent in CNNs: What is Chain Rule
Gradient Descent in CNNs: Applying Chain Rule
Gradient Descent in CNNs: Gradients of Convolutional Layer
Gradient Descent in CNNs: Extending to Multiple Filters
Gradient Descent in CNNs: Gradients of MaxPooling Layer
Gradient Descent in CNNs: Extending to Multiple Layers
Gradient Descent in CNNs: Implementation in NumPy ForwardPass.mp4.
Gradient Descent in CNNs: Implementation in NumPy BackwardPass 1
Gradient Descent in CNNs: Implementation in NumPy BackwardPass 2
Gradient Descent in CNNs: Implementation in NumPy BackwardPass 3
Gradient Descent in CNNs: Implementation in NumPy BackwardPass 4
Gradient Descent in CNNs: Implementation in NumPy BackwardPass 5
Gradient Descent in CNNs: Gradient Descent in CNNs Activity
Introduction to TensorFlow: Introduction
Introduction to TensorFlow: FashionMNIST Example Plan Neural Network
Introduction to TensorFlow: FashionMNIST Example CNN
Introduction to TensorFlow: Introduction to TensorFlow Activity
Classical CNNs: LeNet
Classical CNNs: AlexNet
Classical CNNs: VGG
Classical CNNs: InceptionNet
Classical CNNs: Google Net
Classical CNNs: Resnet
Classical CNNs: Classical CNNs Activity
Transfer Learning: What is Transfer learning
Transfer Learning: Why Transfer Learning
Transfer Learning: ImageNet Challenge
Transfer Learning: Practical Tips
Transfer Learning: Project in TensorFlow
Transfer Learning: Transfer Learning Activity
Yolo: Image Classification Revisited
Yolo: Sliding Window Object Localization
Yolo: Sliding Window Efficient Implementation
Yolo: Yolo Introduction
Yolo: Yolo Training Data Generation
Yolo: Yolo Anchor Boxes
Yolo: Yolo Algorithm
Yolo: Yolo Non-Maxima Suppression
Yolo: RCNN
Yolo: Yolo Activity
Face Verification: Problem Setup
Face Verification: Project Implementation
Face Verification: Face Verification Activity
Neural Style Transfer: Problem Setup
Neural Style Transfer: Implementation TensorFlow Hub
Chapter 9 : Deep learning: Recurrent Neural Networks with Python
Introduction
Applications of RNN (Motivation): Human Activity Recognition
Applications of RNN (Motivation): Image Captioning
Applications of RNN (Motivation): Machine Translation
Applications of RNN (Motivation): Speech Recognition
Applications of RNN (Motivation): Stock Price Predictions
Applications of RNN (Motivation): When to Model RNN
Applications of RNN (Motivation): Activity
RNN Architecture: Introduction to Module
RNN Architecture: Fixed Length Memory Model
RNN Architecture: Fixed Length Memory Model Exercise
RNN Architecture: Fixed Length Memory Model Exercise Solution Part 01
RNN Architecture: Fixed Length Memory Model Exercise Solution Part 02
RNN Architecture: Infinite Memory Architecture
RNN Architecture: Infinite Memory Architecture Exercise
RNN Architecture: Infinite Memory Architecture Solution
RNN Architecture: Weight Sharing
RNN Architecture: Notations
RNN Architecture: ManyToMany Model
RNN Architecture: ManyToMany Model Exercise 01
RNN Architecture: ManyToMany Model Solution 01
RNN Architecture: ManyToMany Model Exercise 02
RNN Architecture: ManyToMany Model Solution 02
RNN Architecture: ManyToOne Model
RNN Architecture: ManyToOne Model Exercise
RNN Architecture: ManyToOne Model Solution
RNN Architecture: OneToMany Model
RNN Architecture: OneToMany Model Exercise
RNN Architecture: OneToMany Model Solution
RNN Architecture: Activity Many to One
RNN Architecture: Activity Many to One Exercise
RNN Architecture: Activity Many to One Solution
RNN Architecture: ManyToMany Different Sizes Model
RNN Architecture: Activity Many to Many Nmt
RNN Architecture: Models Summary
RNN Architecture: Deep RNNs
RNN Architecture: Deep RNNs Exercise
RNN Architecture: Deep RNNs Solution
Gradient Descent in RNN: Introduction to Gradient Descent Module
Gradient Descent in RNN: Example Setup
Gradient Descent in RNN: Equations
Gradient Descent in RNN: Equations Exercise
Gradient Descent in RNN: Equations Solution
Gradient Descent in RNN: Loss Function
Gradient Descent in RNN: Why Gradients
Gradient Descent in RNN: Why Gradients Exercise
Gradient Descent in RNN: Why Gradients Solution
Gradient Descent in RNN: Chain Rule
Gradient Descent in RNN: Chain Rule in Action
Gradient Descent in RNN: Backpropagation Through Time
Gradient Descent in RNN: Activity
RNN Implementation: Automatic Differentiation
RNN Implementation: Automatic Differentiation PyTorch
RNN Implementation: Language Modelling Next Word Prediction Vocabulary Index
RNN Implementation: Language Modelling Next Word Prediction Vocabulary Index Embeddings
RNN Implementation: Language Modelling Next Word Prediction RNN Architecture
RNN Implementation: Language Modelling Next Word Prediction Python 1
RNN Implementation: Language Modelling Next Word Prediction Python 2
RNN Implementation: Language Modelling Next Word Prediction Python 3
RNN Implementation: Language Modelling Next Word Prediction Python 4
RNN Implementation: Language Modelling Next Word Prediction Python 5
RNN Implementation: Language Modelling Next Word Prediction Python 6
Sentiment Classification using RNN: Vocabulary Implementation
Sentiment Classification using RNN: Vocabulary Implementation Helpers
Sentiment Classification using RNN: Vocabulary Implementation from File
Sentiment Classification using RNN: Vectorizer
Sentiment Classification using RNN: RNN Setup 1
Sentiment Classification using RNN: RNN Setup 2
Sentiment Classification using RNN: What Next
Vanishing Gradients in RNN: Introduction to Better RNNs Module
Vanishing Gradients in RNN: Introduction Vanishing Gradients in RNN
Vanishing Gradients in RNN: GRU
Vanishing Gradients in RNN: GRU Optional
Vanishing Gradients in RNN: LSTM
Vanishing Gradients in RNN: LSTM Optional
Vanishing Gradients in RNN: Bidirectional RNN
Vanishing Gradients in RNN: Attention Model
Vanishing Gradients in RNN: Attention Model Optional
TensorFlow: Introduction to TensorFlow
TensorFlow: TensorFlow Text Classification Example using RNN
Project I_ Book Writer: Introduction
Project I_ Book Writer: Data Mapping
Project I_ Book Writer: Modelling RNN Architecture
Project I_ Book Writer: Modelling RNN Model in TensorFlow
Project I_ Book Writer: Modelling RNN Model Training
Project I_ Book Writer: Modelling RNN Model Text Generation
Project I_ Book Writer: Activity
Project II_ Stock Price Prediction: Problem Statement
Project II_ Stock Price Prediction: Dataset
Project II_ Stock Price Prediction: Data Preparation
Project II_ Stock Price Prediction: RNN Model Training and Evaluation
Project II_ Stock Price Prediction: Activity
Further Readings and Resources: Further Readings and Resources