2023: Deep Learning Mastery With Tensorflow & Keras

سرفصل های دوره

Tensorflow & Keras + FFN, CNN, RNN, LSTM, GRU, GAN, Autoencoders, Transfer Learning, Data Augmentation, Text/Image Model

1. Introduction

1. Course Introduction

2. 02 Introduction to Tensorflow and Keras

3. 03 Google Collab setup

2. Tensorflow

1. 04 Tensors Intuition

2.1 01 tensorflow basics class tensors variables.zip

2. 05 Tensors Code it!

3. 06 Tensors Basics Code

4. 07 Tensorflow Variables

5.1 exercise 1 problems solutions.zip

5. 08 Tensors & Variables Exercise & Solutions

6.1 02 graphs and tf.functions.zip

6. 09 Eager Vs Graph execution

7. 10 Tf function Decorator

3. Deep Learning Model Development Basics

1. 11 Intuition Neural Networks

2. 12 NeuralNetworks

3. 13 Approach to Deep Learning problems

4. 14 Lifecycle of model 5 steps

5. 15 Sequential Vs Functional API

4. How to implement First Deep Learning Model

1.1 03 model building - seq vs functional api.zip

1. 16 Sequential API

2. 17 Functional API

3. 18 ML problem Cost Gradient CV

4. 19 Activation Functions

5. 20 Optimizers

6. 21 Loss functions

7. 22 Performance Metrics

8. 23 Tips for Improving Model Performance

5. Feed Forward Networks

1.1 04 feed forward networks.zip

1. 24 Feed Forward Network Implementation and Keras Callbacks

6. CONVOLUTIONAL NEURAL NETWORK (CNN)

1. 25 Intro to CNN

2.1 05 cnn with cifar10.zip

2. 26 CNN implementation

3. 27 CNN Exercise -2 Problem

4.1 exercise 2. mnist classifier using cnn.zip

4. 28 CNN Exercise -2 Solution

5. 29 CNN Exercise -3 Problem

6.1 exercise 3. fashion-mnist classifier using cnn.zip

6. 30 CNN Exercise -3 Solution

7. Keras Preprocessing Layers

1. 31 Keras Preprocessing Layers Intro

2.1 06 keras preprocessing layers.zip

2. 32 Keras Preprocessing Layers Image Augmentation Code

3. 33 Keras Preprocessing Layers Text Preprocessing Code

4. 34 Keras Preprocessing Layers Exercise

5.1 exercise-4 keras preprocessing layer cats n dogs.zip

5. 35 Keras Preprocessing Layers Solution

8. Transfer Learning

1. 36 Transfer Learning

2.1 07 transfer learning on cats and dogs dataset.zip

2. 37 Transfer Learning code

3. 38 Transfer Learning Exercise Xray Dataset

4.1 exercise 5- transfer learning chest xray dataset.zip

4. 39 Transfer Learning Solution XrayDataset

9. Sequential Models (Numeric Data)

1. RNN Explained

2. LSTM & GRU Explained

3.1 08 lstm time series univariate.zip

3. 41 RNN LSTM Univariate Time Series

4.1 09 lstm multiple time series.zip

4. 42 RNN LSTM Multiple Time Series

10. Sequential Models (Text Data)

1. 43 types of Text embeddings

2.1 10 text embeddings.zip

2. 44 Text embeddings importing

3.1 11 text embeddings lstm classifier.zip

3. 45 RNN LSTM Text embedding for classification

11. Autoencoders

1. 46 Autoencoder

2.1 12 autoencoders dimensionality reduction.zip

2. 47 Autoencoder Dimensionality Reduction

3. 48 Autoencoder Anomaly detection exercise

4.1 exercise 6 anomaly detection using autoencoders.zip

4. 49 Autoencoder Anomaly detection solution

12. GENERATIVE ADVERSARIAL NETWORKS (GANs)

1. 50 GANs Introduction

2. 51 GANs components

3. 52 GANs Training

4. 53 GANs Applications Pros & Cons

5.1 13 gan fashion mnist generator.zip

5. 54 GANs implementation

13. CAPSTONE Project

1. Project Image Captioning Problem

2.1 14 project 1 image captioning.zip

2. Project Image Captioning Solution Part-1

3. Project Image Captioning Solution Part-2

4. Project Image Captioning Solution Part-3

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تولید کننده: Udemy