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Mastering Deep Learning with Python

Name: Mastering Deep Learning with Python
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A comprehensive course covering the foundations of deep learning and neural networks, computer vision, and advanced techniques, through to real-world and creative applications including text and sequence data, based on Deep Learning with Python by Francois Chollet.

See the syllabus

17chapters

48modules

139lessons

28quizzes

Syllabus

17 chapters, 48 modules, 167 lessons and quizzes.

01Foundations of Deep Learning2 modules · 6 lessons
Understanding Deep Learning Basics
Neural Network Fundamentals
02Accessing Support Resources1 modules · 3 lessons
Using the Private Web Forum
03Introduction to Deep Learning1 modules · 1 lessons
Overview of Part 1
- LessonCourse Structure and ObjectivesEnroll to open
04Foundational Concepts in Deep Learning1 modules · 1 lessons
Introduction to Fundamentals
- LessonUnderstanding Deep Learning FundamentalsEnroll to open
05Introduction to Deep Learning: Canonical workflow for solving data problems using deep learning1 modules · 5 lessons
Understanding Deep Learning Fundamentals
06Introduction to Deep Learning: Artificial Intelligence3 modules · 11 lessons
Why Deep Learning Now?
Understanding AI, Machine Learning, and Deep Learning
History of Machine Learning
07Getting Started with Deep Learning4 modules · 11 lessons
Course Structure and Roadmap
Prerequisites and Target Audience
Software and Hardware Requirements
Accessing the Source Code
- LessonDownloading Code ExamplesEnroll to open
08Advanced Deep Learning Techniques1 modules · 1 lessons
Introduction to Advanced Deep Learning
- LessonOverview of Advanced Deep Learning TopicsEnroll to open
09Computer Vision with Deep Learning3 modules · 10 lessons
Introduction to Convolutional Neural Networks
Training a Convnet on a Small Dataset
Using Pretrained Convnets
- LessonFeature Extraction with Pretrained ConvnetsEnroll to open
- QuizPretrained Convnets QuizEnroll to open
10Introduction to Neural Networks3 modules · 9 lessons
Understanding Neural Network Components
Introduction to Keras and Workstation Setup
- LessonKeras OverviewEnroll to open
- LessonSetting Up a Deep-Learning WorkstationEnroll to open
Practical Examples with Keras
11Mathematical Foundations of Neural Networks4 modules · 19 lessons
Tensors and Tensor Operations
Tensor Operations in Neural Networks
Introduction to Neural Networks
Gradient-Based Optimization
12Machine Learning Essentials5 modules · 19 lessons
Branches of Machine Learning
Evaluating Machine Learning Models
Data Preprocessing and Feature Engineering
Overfitting and Underfitting
The Universal Workflow of Machine Learning
13Applying Deep Learning in Real-World Scenarios3 modules · 7 lessons
Introduction to Convolutional Neural Networks
- LessonUnderstanding Convolutional Neural NetworksEnroll to open
Techniques for Improving Convolutional Neural Networks
Visualizing Convolutional Neural Networks
- LessonUnderstanding Convnet Decisions Through VisualizationEnroll to open
- LessonConvnet Visualization PracticeEnroll to open
14Advanced Techniques for Deep Learning Models3 modules · 10 lessons
Building Complex Models with the Keras Functional API
Monitoring and Controlling Model Training
- LessonUsing Callbacks to Monitor and Control TrainingEnroll to open
- LessonVisualizing Model Performance with TensorBoardEnroll to open
Advanced Model Optimization Techniques
15Creative Applications of Deep Learning5 modules · 15 lessons
Text Generation with LSTM
DeepDream
- LessonHow DeepDream Turns Learned Features into Visual PatternsEnroll to open
- LessonDeepDream PracticeEnroll to open
Neural Style Transfer
Variational Autoencoders
Generative Adversarial Networks
16Creative Applications of Deep Learning: Convnets4 modules · 14 lessons
Text Generation with LSTM
Variational Autoencoders and GANs
DeepDream
- LessonDeepDream AlgorithmEnroll to open
- LessonImplementing DeepDream in KerasEnroll to open
Neural Style Transfer
17Deep Learning for Text and Sequence Data4 modules · 25 lessons
Text Preprocessing and Word Embeddings
Recurrent Neural Networks
Advanced Use of Recurrent Neural Networks
Sequence Processing with Convnets

Start Mastering Deep Learning with Python today.

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Mastering Deep Learning with Python

Mastering Deep Learning with Python

Syllabus

Understanding Deep Learning Basics

Neural Network Fundamentals

Using the Private Web Forum

Overview of Part 1

Introduction to Fundamentals

Understanding Deep Learning Fundamentals

Why Deep Learning Now?

Understanding AI, Machine Learning, and Deep Learning

History of Machine Learning

Course Structure and Roadmap

Prerequisites and Target Audience

Software and Hardware Requirements

Accessing the Source Code

Introduction to Advanced Deep Learning

Introduction to Convolutional Neural Networks

Training a Convnet on a Small Dataset

Using Pretrained Convnets

Understanding Neural Network Components

Introduction to Keras and Workstation Setup

Practical Examples with Keras

Tensors and Tensor Operations

Tensor Operations in Neural Networks

Introduction to Neural Networks

Gradient-Based Optimization

Branches of Machine Learning

Evaluating Machine Learning Models

Data Preprocessing and Feature Engineering

Overfitting and Underfitting

The Universal Workflow of Machine Learning

Introduction to Convolutional Neural Networks

Techniques for Improving Convolutional Neural Networks

Visualizing Convolutional Neural Networks

Building Complex Models with the Keras Functional API

Monitoring and Controlling Model Training

Advanced Model Optimization Techniques

Text Generation with LSTM

DeepDream

Neural Style Transfer

Variational Autoencoders

Generative Adversarial Networks

Text Generation with LSTM

Variational Autoencoders and GANs

DeepDream

Neural Style Transfer

Text Preprocessing and Word Embeddings

Recurrent Neural Networks

Advanced Use of Recurrent Neural Networks

Sequence Processing with Convnets

Start Mastering Deep Learning with Python today.