Deep Learning CNN with Python Online Course
Deep Learning CNN with Python Online Course
This course provides a comprehensive understanding of Convolutional Neural Networks (CNNs), a crucial tool in computer vision and data science. You'll start with image processing and object detection, followed by deep neural networks concepts like perceptrons and multi-layered perceptrons. The course covers CNN architecture, gradient descent, TensorFlow, classical CNN models, transfer learning, and a YOLO case study. You'll also work on two hands-on projects: Neural Style Transfer and Face Verification. By the end, you'll master CNNs for data science and apply them to real-world datasets.
Who is this Course for?
This course is ideal for beginners in data science and deep learning who want to learn CNNs using real datasets and apply them to practical projects. No prior experience is required—you'll start from the basics and gradually build your expertise. All you need is a willingness to learn and practice to master CNNs and their applications in data science.
What you will learn
- Learn the importance of CNNs in data science
- Understand the shift from classical vision to CNNs
- Master concepts with Python examples
- Explore CNN evolution from LeNet to MobileNets
- Train CNNs from scratch with hands-on practice
- Build projects on face verification & neural style transfer
Course Table of Contents
Introduction to the Course
- Course Overview
- Introduction to Instructor
- Why CNN
- Focus of the Course
Image Processing
- Gray-Scale Images
- Gray-Scale Images Quiz
- Gray-Scale Images Solution
- RGB Images
- RGB Images Quiz
- RGB Images Solution
- Reading and Showing Images in Python
- Reading and Showing Images in Python Quiz
- Reading and Showing Images in Python Solution
- Converting an Image to Grayscale in Python
- Converting an Image to Grayscale in Python Quiz
- Converting an Image to Grayscale in Python Solution
- Image Formation
- Image Formation Quiz
- Image Formation Solution
- Image Blurring 1
- Image Blurring 1 Quiz
- Image Blurring 1 Solution
- Image Blurring 2
- Image Blurring 2 Quiz
- Image Blurring 2 Solution
- General Image Filtering
- Convolution
- Edge Detection
- Image Sharpening
- Implementation of Image Blurring Edge Detection Image Sharpening in Python
- Parametric Shape Detection
- Image Processing
- Image Processing Activity
- Image Processing Activity Solution
Object Detection
- Introduction to Object Detection
- Classification Pipeline
- Classification Pipeline Quiz
- Classification Pipeline Solution
- Sliding Window Implementation
- Shift Scale Rotation Invariance
- Shift Scale Rotation Invariance Exercise
- Person Detection
- HOG Features
- HOG Features Exercise
- Hand Engineering Versus CNNs
- Object Detection Activity
Deep Neural Network Overview
- Neuron and Perceptron
- DNN Architecture
- DNN Architecture Quiz
- DNN Architecture Solution
- FeedForward FullyConnected MLP
- Calculating Number of Weights of DNN
- Calculating Number of Weights of DNN Quiz
- Calculating Number of Weights of DNN Solution
- Number of Neurons Versus Number of Layers
- Discriminative Versus Generative Learning
- Universal Approximation Theorem
- Why Depth
- Decision Boundary in DNN
- Decision Boundary in DNN Quiz
- Decision Boundary in DNN Solution
- BiasTerm
- BiasTerm Quiz
- BiasTerm Solution
- Activation Function
- Activation Function Quiz
- Activation Function Solution
- DNN Training Parameters
- DNN Training Parameters Quiz
- DNN Training Parameters Solution
- Gradient Descent
- Backpropagation
- Training DNN Animation
- Weight Initialization
- Weight Initialization Quiz
- Weight Initialization Solution
- Batch MiniBatch Stochastic Gradient Descent
- Batch Normalization
- Rprop and Momentum
- Rprop and Momentum Quiz
- Rprop and Momentum Solution
- Convergence Animation
- DropOut, Early Stopping and Hyperparameters
- DropOut, Early Stopping and Hyperparameters Quiz
- DropOut, Early Stopping and Hyperparameters Solution
Deep Neural Network Architecture
- Convolution Revisited
- Implementing Convolution in Python Revisited
- Why Convolution
- Filters Padding Strides
- Padding Image
- Pooling Tensors
- CNN Example
- Convolution and Pooling Details
- MaxPooling Exercise
- NonVectorized Implementations of Conv2d and Pool2d
- Deep Neural Network Architecture Activity
Gradient Descent in CNNs
- Example Setup
- Why Derivatives
- Why Derivatives Quiz
- Why Derivatives Solution
- What Is Chain Rule
- Applying Chain Rule
- Gradients of MaxPooling Layer
- Gradients of MaxPooling Layer Quiz
- Gradients of MaxPooling Layer Solution
- Gradients of Convolutional Layer
- Extending to Multiple Filters
- Extending to Multiple Layers
- Extending to Multiple Layers Quiz
- Extending to Multiple Layers Solution
- Implementation in NumPy ForwardPass
- Implementation in NumPy BackwardPass 1
- Implementation in NumPy BackwardPass 2
- Implementation in NumPy BackwardPass 3
- Implementation in NumPy BackwardPass 4
- Implementation in NumPy BackwardPass 5
- Gradient Descent in CNNs Activity
Introduction to TensorFlow
- Introduction to TensorFlow
- FashionMNIST Example Plan Neural Network
- FashionMNIST Example CNN
- Introduction to TensorFlow Activity
Classical CNNs
- LeNet
- LeNet Quiz
- LeNet Solution
- AlexNet
- VGG
- InceptionNet
- GoogLeNet
- Resnet
- Classical CNNs Activity
Transfer Learning
- What Is Transfer learning
- Why Transfer Learning
- ImageNet Challenge
- Practical Tips
- Project in TensorFlow
- Transfer Learning Activity
YOLO
- Image Classification Revisited
- Sliding Window Object Localization
- Sliding Window Efficient Implementation
- YOLO Introduction
- YOLO Training Data Generation
- YOLO Anchor Boxes
- YOLO Algorithm
- YOLO Non-Maxima Suppression
- RCNN
- YOLO Activity
Face Verification
- Problem Setup
- Project Implementation
- Face Verification Activity
Neural Style Transfer
- Problem Setup
- Implementation TensorFlow Hub
- Thank You and Conclusion
