Python & TensorFlow: Deep Dive into Machine Learning

سرفصل های دوره

Python & TensorFlow: The Roadmap to Deep Machine Learning Expertise

1. Introduction to Machine & Deep Learning

1. What is Machine Learning

2. Types of Machine Learning

3. Applications of Machine Learning

4. What is Deep Learning

2. Basics of TensorFlow & Installation

1. What is TensorFlow

2. Installing and Setting up TensorFlow

3. TensorFlow Architecture

4. A refresher on APIs

5. TensorFlow APls

3. Machine Learning Part 1 Supervised Learning

1. What is Supervised Learning

2. Linear Regression

3. Logistic Regression

4. Decision Trees

5. Random Forests

6. Support Vector Machines (SVMs)

4. Machine Learning Part 2 Unsupervised Learning

1. What is Unsupervised Learning

2. K-Means Clustering

3. Hierarchical Clustering

4. Principal Component Analysis (PCA)

5. Deep Learning Basics with Tensorflow Neural Networks

1. What are Neural Networks

2. Basic Neural Networks

3. Convolutional Neural Networks (CNNs)

4. Recurrent Neural Networks (RNNs)

5. Building Deep Neural Networks

6. Model Evaluation & Optimization

1. Training and Testing Data

2. Model Evaluation Metrics

3. Overfitting and Underfitting

4. Hyperparameter Tuning

7. TensorFlow for Production

1. Saving and restoring models

2. Deploying TensorFlow models

3. Distributed TensorFlow

4. TensorBoard for visualization and debugging

8. Project Image Classification

1. ML Project Image classification Model

9. Conclusion

1. Conclusion

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تولید کننده: Udemy