深度学习 - 使用 Python 中的神经网络案例研究
上次更新时间：2024-10-15
课程售价: 2.9 元
联系右侧微信客服充值或购买课程
课程内容
1 - Deep Learning Convolutional Neural Network CNN using Python
- 1 - Introduction of Project (免费)
- 2 - Overview of CNN (免费)
- 3 - Installations and Dataset Structure
- 4 - Import libraries
- 5 - CNN Model and Layers Coding
- 6 - Data Preprocessing and Augmentation
- 7 - Understanding Data generator
- 8 - Prediction on Single Image
- 9 - Understanding Different Models and Accuracy
2 - Deep Learning Artificial Neural Network ANN using Python
- 10 - Introduction of Project
- 11 - Setup Environment for ANN
- 12 - ANN Installation
- 13 - Import Libraries and Data Preprocessing
- 14 - Data Preprocessing
- 15 - Data Preprocessing Continue
- 16 - Data Exploration
- 17 - Encoding
- 18 - Encoding Continue
- 19 - Preparation of Dataset for Training
- 20 - Steps to Build ANN Part 1
- 21 - Steps to Build ANN Part 2
- 22 - Steps to Build ANN Part 3
- 23 - Steps to Build ANN Part 4
- 24 - Predictions
- 25 - Predictions Continue
- 26 - Resampling Data with ImbalanceLearn
- 27 - Resampling Data with ImbalanceLearn Continue
3 - Deep Learning RNN LSTM Stock Price Prognostics using Python
- 28 - Introduction of Project
- 29 - Installation
- 30 - Libraries
- 31 - Dataset Explore
- 32 - Import Libraries
- 33 - Data Preprocessing
- 34 - Exploratory Data Analysis
- 35 - Exploratory Data Analysis Continue
- 36 - Feature Scaling
- 37 - Feature Scaling Continue
- 38 - More on Feature Scaling
- 39 - Building RNN
- 40 - Building RNN Continue
- 41 - Training of Network
- 42 - Prediction on Test Data
- 43 - Prediction on Test Data Continue
- 44 - Final Result Visualization
4 - Deep Learning Project using Convolutional Neural Network CNN in Python
课程内容
4个章节 , 51个讲座
1 - Deep Learning Convolutional Neural Network CNN using Python
- 1 - Introduction of Project (免费)
- 2 - Overview of CNN (免费)
- 3 - Installations and Dataset Structure
- 4 - Import libraries
- 5 - CNN Model and Layers Coding
- 6 - Data Preprocessing and Augmentation
- 7 - Understanding Data generator
- 8 - Prediction on Single Image
- 9 - Understanding Different Models and Accuracy
2 - Deep Learning Artificial Neural Network ANN using Python
- 10 - Introduction of Project
- 11 - Setup Environment for ANN
- 12 - ANN Installation
- 13 - Import Libraries and Data Preprocessing
- 14 - Data Preprocessing
- 15 - Data Preprocessing Continue
- 16 - Data Exploration
- 17 - Encoding
- 18 - Encoding Continue
- 19 - Preparation of Dataset for Training
- 20 - Steps to Build ANN Part 1
- 21 - Steps to Build ANN Part 2
- 22 - Steps to Build ANN Part 3
- 23 - Steps to Build ANN Part 4
- 24 - Predictions
- 25 - Predictions Continue
- 26 - Resampling Data with ImbalanceLearn
- 27 - Resampling Data with ImbalanceLearn Continue
3 - Deep Learning RNN LSTM Stock Price Prognostics using Python
- 28 - Introduction of Project
- 29 - Installation
- 30 - Libraries
- 31 - Dataset Explore
- 32 - Import Libraries
- 33 - Data Preprocessing
- 34 - Exploratory Data Analysis
- 35 - Exploratory Data Analysis Continue
- 36 - Feature Scaling
- 37 - Feature Scaling Continue
- 38 - More on Feature Scaling
- 39 - Building RNN
- 40 - Building RNN Continue
- 41 - Training of Network
- 42 - Prediction on Test Data
- 43 - Prediction on Test Data Continue
- 44 - Final Result Visualization