Deep Learning: Neural Networks in Python using Case Studies

سرفصل های دوره

Learn how a neural network is built from basic building blocks using Python

1 - Deep Learning Convolutional Neural Network CNN using Python

1 - Introduction of Project

2 - Overview of CNN

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

45 - Introduction to Project

46 - Google Collab

47 - Importing Packages and Data

48 - Preprocessing and Model Creation

49 - Training the Model and Prediction

50 - Model Creation using CNN

51 - CNN Model Prediction

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تولید کننده: Udemy