【中英双语】TensorFlow 2.0 大师班：动手深度学习和人工智能

参与 6 个项目，动手实践 TensorFlow 2.0、Keras、深度学习和人工智能！此教程共15小时，中英双语字幕，画质清晰无水印，源码附件全课程英文名：TensorFlow 2.0 Masterclass Hands-On Deep Learning and AI

下载地址

百度网盘地址：https://pan.baidu.com/s/1Jh_qGA8YYXf5Azss9hpE1w?pwd=tp4m

课程内容

你将会学到的

从零开始全面理解 TensorFlow 2.0
人工神经网络 (ANN)
卷积神经网络 (CNN)
递归神经网络 (RNN)
迁移学习
自然语言处理
使用 Numpy、Pandas 进行数据分析和使用 Matplotlib 进行数据可视化

项目清单，

项目 1：用于数字识别的 CNN

项目 2：用于乳腺癌检测的 CNN

项目 3：用于预测银行客户满意度的 CNN

项目 4：用于信用卡欺诈检测的 CNN

项目 5：RNN - 用于 IMDB 评论分类的 LSTM

项目 6：使用 RNN 和 LSTM 预测谷歌股票价格

本课程涵盖的主要主题，

第 1 部分：简介（第 1 部分）

第 2 部分：人工神经网络（第 2 节 - 第 4 节）

第 3 部分：卷积神经网络（第 5 节 - 第 11 节）

第 4 部分：循环神经网络（第 12 节 - 第 15 节）

第 5 部分：迁移学习

第 6 部分：自然语言处理（第 16 节）

第 7 部分：使用 Numpy、Pandas 进行数据分析和使用 Matplotlib 进行数据可视化（第 17 节 - 第 19 节）

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├── 01 Welcome to the Course !
│   ├── 001 Course Overview !.html
│   ├── 002 Introduction to Google Colab.en.srt
│   ├── 002 Introduction to Google Colab.mp4
│   └── 003 Links to TensorFlow Notebooks.html
├── 02 Introduction to Artificial Neural Networks (ANNs)
│   ├── 004 The Neuron.en.srt
│   ├── 004 The Neuron.mp4
│   ├── 005 Activation Function.en.srt
│   ├── 005 Activation Function.mp4
│   ├── 006 Cost Function.en.srt
│   ├── 006 Cost Function.mp4
│   ├── 007 Gradient Descent and Back-Propagation.en.srt
│   └── 007 Gradient Descent and Back-Propagation.mp4
├── 03 Building the Artificial Neural Networks (ANNs)
│   ├── 008 Step 1 - Installation and Setup.en.srt
│   ├── 008 Step 1 - Installation and Setup.mp4
│   ├── 009 Step 2 - Data Preprocessing.en.srt
│   ├── 009 Step 2 - Data Preprocessing.mp4
│   ├── 010 Step 3 - Building the Model.en.srt
│   ├── 010 Step 3 - Building the Model.mp4
│   ├── 011 Step 4 - Training the Model.en.srt
│   ├── 011 Step 4 - Training the Model.mp4
│   ├── 012 Step 5 - Model evaluation and performance.en.srt
│   └── 012 Step 5 - Model evaluation and performance.mp4
├── 04 Binary Classification with Artificial Neural Networks
│   ├── 013 Step 1 - Binary Classification.en.srt
│   ├── 013 Step 1 - Binary Classification.mp4
│   ├── 014 Step 2 - Binary Classification.en.srt
│   ├── 014 Step 2 - Binary Classification.mp4
│   ├── 015 Step 3 - Binary Classification.en.srt
│   ├── 015 Step 3 - Binary Classification.mp4
│   ├── 016 Step 4 - Binary Classification.en.srt
│   ├── 016 Step 4 - Binary Classification.mp4
│   ├── 017 Step 5 - Binary Classification.en.srt
│   └── 017 Step 5 - Binary Classification.mp4
├── 05 Introduction to Convolutional Neural Networks (CNNs)
│   ├── 018 Convolutional Neural Network Part 1.en.srt
│   ├── 018 Convolutional Neural Network Part 1.mp4
│   ├── 019 Convolutional Neural Network Part 1.en.srt
│   └── 019 Convolutional Neural Network Part 1.mp4
├── 06 Building Convolutional Neural Networks (CNNs)
│   ├── 020 Building Convolutional Neural Network Step 1.en.srt
│   ├── 020 Building Convolutional Neural Network Step 1.mp4
│   ├── 021 Building Convolutional Neural Network Step 2.en.srt
│   ├── 021 Building Convolutional Neural Network Step 2.mp4
│   ├── 022 Building Convolutional Neural Network Step 3.en.srt
│   ├── 022 Building Convolutional Neural Network Step 3.mp4
│   ├── 023 Building Convolutional Neural Network Step 4.en.srt
│   ├── 023 Building Convolutional Neural Network Step 4.mp4
│   ├── 024 Building Convolutional Neural Network Step 5.en.srt
│   └── 024 Building Convolutional Neural Network Step 5.mp4
├── 07 CNN for Binary Image Classification
│   ├── 025 CNN for Binary Image Classification Step 1.en.srt
│   ├── 025 CNN for Binary Image Classification Step 1.mp4
│   ├── 026 CNN for Binary Image Classification Step 2.en.srt
│   ├── 026 CNN for Binary Image Classification Step 2.mp4
│   ├── 027 CNN for Binary Image Classification Step 3.en.srt
│   ├── 027 CNN for Binary Image Classification Step 3.mp4
│   ├── 028 CNN for Binary Image Classification Step 4.en.srt
│   ├── 028 CNN for Binary Image Classification Step 4.mp4
│   ├── 029 CNN for Binary Image Classification Step 5.en.srt
│   └── 029 CNN for Binary Image Classification Step 5.mp4
├── 08 Project 1_ CNN for Digit Recognition
│   ├── 030 CNN for Digit Recognition Part 1.en.srt
│   ├── 030 CNN for Digit Recognition Part 1.mp4
│   ├── 031 CNN for Digit Recognition Part 2.en.srt
│   ├── 031 CNN for Digit Recognition Part 2.mp4
│   ├── 032 CNN for Digit Recognition Part 3.en.srt
│   └── 032 CNN for Digit Recognition Part 3.mp4
├── 09 Project 2_ CNN for Breast Cancer Detection
│   ├── 033 CNN for Breast Cancer Detection Part 1.en.srt
│   ├── 033 CNN for Breast Cancer Detection Part 1.mp4
│   ├── 034 CNN for Breast Cancer Detection Part 2.en.srt
│   ├── 034 CNN for Breast Cancer Detection Part 2.mp4
│   ├── 035 CNN for Breast Cancer Detection Part 3.en.srt
│   └── 035 CNN for Breast Cancer Detection Part 3.mp4
├── 10 Project 3_ CNN for Predicting the Bank Customer Satisfaction
│   ├── 036 CNN for Predicting the Bank Customer Satisfaction Part 1.en.srt
│   ├── 036 CNN for Predicting the Bank Customer Satisfaction Part 1.mp4
│   ├── 037 CNN for Predicting the Bank Customer Satisfaction Part 2.en.srt
│   ├── 037 CNN for Predicting the Bank Customer Satisfaction Part 2.mp4
│   ├── 038 CNN for Predicting the Bank Customer Satisfaction Part 3.en.srt
│   ├── 038 CNN for Predicting the Bank Customer Satisfaction Part 3.mp4
│   ├── 039 CNN for Predicting the Bank Customer Satisfaction Part 4.en.srt
│   └── 039 CNN for Predicting the Bank Customer Satisfaction Part 4.mp4
├── 11 Project 4_ CNN for Credit Card Fraud Detection
│   ├── 040 CNN for Credit Card Fraud Detection Part 1.en.srt
│   ├── 040 CNN for Credit Card Fraud Detection Part 1.mp4
│   ├── 041 CNN for Credit Card Fraud Detection Part 2.en.srt
│   ├── 041 CNN for Credit Card Fraud Detection Part 2.mp4
│   ├── 042 CNN for Credit Card Fraud Detection Part 3.en.srt
│   ├── 042 CNN for Credit Card Fraud Detection Part 3.mp4
│   ├── 043 CNN for Credit Card Fraud Detection Part 4.en.srt
│   └── 043 CNN for Credit Card Fraud Detection Part 4.mp4
├── 12 Recurrent Neural Networks (RNNs)
│   ├── 044 Introduction to Recurrent Neural Networks.en.srt
│   ├── 044 Introduction to Recurrent Neural Networks.mp4
│   ├── 045 Vanishing Gradient Problem.en.srt
│   ├── 045 Vanishing Gradient Problem.mp4
│   ├── 046 LSTM and GRU.en.srt
│   └── 046 LSTM and GRU.mp4
├── 13 Project 5_ RNN - LSTM for IMDB Review Classification
│   ├── 047 RNN - LSTM for IMDB Review Classification Part 1.en.srt
│   ├── 047 RNN - LSTM for IMDB Review Classification Part 1.mp4
│   ├── 048 RNN - LSTM for IMDB Review Classification Part 2.en.srt
│   ├── 048 RNN - LSTM for IMDB Review Classification Part 2.mp4
│   ├── 049 RNN - LSTM for IMDB Review Classification Part 3.en.srt
│   └── 049 RNN - LSTM for IMDB Review Classification Part 3.mp4
├── 14 RNN - LSTM for Image Classification
│   ├── 050 RNN - LSTM for Image Classification Part 1.en.srt
│   ├── 050 RNN - LSTM for Image Classification Part 1.mp4
│   ├── 051 RNN - LSTM for Image Classification Part 2.en.srt
│   ├── 051 RNN - LSTM for Image Classification Part 2.mp4
│   ├── 052 RNN - LSTM for Image Classification Part 3.en.srt
│   └── 052 RNN - LSTM for Image Classification Part 3.mp4
├── 15 Project 6_ Google Stock Price Prediction with RNN and LSTM
│   ├── 053 Google Stock Price Prediction with RNN and LSTM Part 1.en.srt
│   ├── 053 Google Stock Price Prediction with RNN and LSTM Part 1.mp4
│   ├── 054 Google Stock Price Prediction with RNN and LSTM Part 2.en.srt
│   ├── 054 Google Stock Price Prediction with RNN and LSTM Part 2.mp4
│   ├── 055 Google Stock Price Prediction with RNN and LSTM Part 3.en.srt
│   ├── 055 Google Stock Price Prediction with RNN and LSTM Part 3.mp4
│   ├── 056 Google Stock Price Prediction with RNN and LSTM Part 4.en.srt
│   ├── 056 Google Stock Price Prediction with RNN and LSTM Part 4.mp4
│   ├── 057 Google Stock Price Prediction with RNN and LSTM Part 5.en.srt
│   └── 057 Google Stock Price Prediction with RNN and LSTM Part 5.mp4
├── 16 Transfer Learning
│   ├── 058 Introduction to Transfer Learning.en.srt
│   ├── 058 Introduction to Transfer Learning.mp4
│   ├── 059 Transfer Learning Part 1.en.srt
│   ├── 059 Transfer Learning Part 1.mp4
│   ├── 060 Transfer Learning Part 2.en.srt
│   ├── 060 Transfer Learning Part 2.mp4
│   ├── 061 Transfer Learning Part 3.en.srt
│   ├── 061 Transfer Learning Part 3.mp4
│   ├── 062 Transfer Learning Part 4.en.srt
│   └── 062 Transfer Learning Part 4.mp4
├── 17 Natural Language Processing
│   ├── 063 Introduction to Natural Language Processing.en.srt
│   ├── 063 Introduction to Natural Language Processing.mp4
│   ├── 064 NLTK Introduction and Installation.en.srt
│   ├── 064 NLTK Introduction and Installation.mp4
│   ├── 065 Tokenization.en.srt
│   ├── 065 Tokenization.mp4
│   ├── 066 Stemming.en.srt
│   ├── 066 Stemming.mp4
│   ├── 067 Lemmatization.en.srt
│   ├── 067 Lemmatization.mp4
│   ├── 068 Stop Words.en.srt
│   ├── 068 Stop Words.mp4
│   ├── 069 POS Tagging.en.srt
│   ├── 069 POS Tagging.mp4
│   ├── 070 Chunking.en.srt
│   ├── 070 Chunking.mp4
│   ├── 071 Named Entity Recognition.en.srt
│   ├── 071 Named Entity Recognition.mp4
│   ├── 072 Text Classification Part 1.en.srt
│   ├── 072 Text Classification Part 1.mp4
│   ├── 073 Text Classification Part 2.en.srt
│   └── 073 Text Classification Part 2.mp4
├── 18 Annex 1_ Data Analysis with Numpy
│   ├── 074 Introduction to NumPy.en.srt
│   ├── 074 Introduction to NumPy.mp4
│   ├── 075 Numpy Arrays Part 1.en.srt
│   ├── 075 Numpy Arrays Part 1.mp4
│   ├── 076 Numpy Arrays Part 2.en.srt
│   ├── 076 Numpy Arrays Part 2.mp4
│   ├── 077 Numpy Arrays Part 3.en.srt
│   ├── 077 Numpy Arrays Part 3.mp4
│   ├── 078 Numpy Indexing and Selection Part 1.en.srt
│   ├── 078 Numpy Indexing and Selection Part 1.mp4
│   ├── 079 Numpy Indexing and Selection Part 2.en.srt
│   ├── 079 Numpy Indexing and Selection Part 2.mp4
│   ├── 080 Numpy Operations.en.srt
│   └── 080 Numpy Operations.mp4
├── 19 Annex 2_ Data Analysis with Pandas
│   ├── 081 Pandas Introduction.en.srt
│   ├── 081 Pandas Introduction.mp4
│   ├── 082 Pandas Series.en.srt
│   ├── 082 Pandas Series.mp4
│   ├── 083 DataFrames Part 1.en.srt
│   ├── 083 DataFrames Part 1.mp4
│   ├── 084 DataFrames Part 2.en.srt
│   ├── 084 DataFrames Part 2.mp4
│   ├── 085 DataFrames Part 3.en.srt
│   ├── 085 DataFrames Part 3.mp4
│   ├── 086 Missing Data.en.srt
│   ├── 086 Missing Data.mp4
│   ├── 087 Groupby Method.en.srt
│   ├── 087 Groupby Method.mp4
│   ├── 088 Merging, Joining and Concatenating DataFrames.en.srt
│   ├── 088 Merging, Joining and Concatenating DataFrames.mp4
│   ├── 089 Pandas Operations.en.srt
│   ├── 089 Pandas Operations.mp4
│   ├── 090 Reading and Writing Files in Pandas.en.srt
│   └── 090 Reading and Writing Files in Pandas.mp4
├── 20 Annex 3_ Data Visualization with Matplotlib
│   ├── 091 Matplotlib Part 1 - Functional Method.en.srt
│   ├── 091 Matplotlib Part 1 - Functional Method.mp4
│   ├── 092 Matplotlib Part 1 - Object Oriented Method.en.srt
│   ├── 092 Matplotlib Part 1 - Object Oriented Method.mp4
│   ├── 093 Matplotlib Part 2 - Subplots Method.en.srt
│   ├── 093 Matplotlib Part 2 - Subplots Method.mp4
│   ├── 094 Matplotlib Part 2 - Figure size, Aspect ratio and DPI.en.srt
│   ├── 094 Matplotlib Part 2 - Figure size, Aspect ratio and DPI.mp4
│   ├── 095 Matplotlib Part 3.en.srt
│   ├── 095 Matplotlib Part 3.mp4
│   ├── 096 Matplotlib Part 4.en.srt
│   └── 096 Matplotlib Part 4.mp4
└── 27.txt20 directories, 191 files