Hands-On Machine Learning with Python: Real Projects

سرفصل های دوره

Master Machine Learning with Python: Build, Train & Deploy Models with Real-World Projects

1 - Introduction to Machine Learning

1 -What is Machine Learning

2 -Types of Machine Learning

3 -Machine Learning Workflow

4 -Python Libraries for Machine Learning

5 -Hands-on Setting up Python Environment

2 - Data Preprocessing

1 -Data Cleaning

2 -Handling Missing Data

3 -Encoding Categorical Data

4 -Feature Scaling

5 -Hands-on Preprocessing Data in Python

3 - Supervised Learning Algorithms

1 -Linear Regression

2 -Logistic Regression

3 -Decision Trees

4 -Support Vector Machines

5 -Hands-on Implementing Algorithms in Python

4 - Unsupervised Learning Algorithms

1 -K-Means Clustering

2 -Hierarchical Clustering

3 -Principal Component Analysis (PCA)

4 -Association Rule Learning

5 -Hands-on Clustering and Dimensionality Reduction in Python

5 - Model Evaluation and Selection

1 -Cross-Validation

2 -Evaluation Metrics

3 -Hyperparameter Tuning

4 -Model Selection

5 -Hands-on Evaluating and Selecting Models in Python

6 - Deep Learning with TensorFlow

1 -Introduction to Neural Networks

2 -TensorFlow Basics

3 -Building Neural Networks in TensorFlow

4 -Convolutional Neural Networks (CNN)

5 -Hands-on Implementing Deep Learning Models in TensorFlow

7 - Natural Language Processing (NLP)

1 -Text Preprocessing

2 -Bag of Words Model

3 -Word Embeddings

4 -Named Entity Recognition

5 -Hands-on NLP Techniques in Python

8 - Deployment and Production

1 -Model Deployment

2 -Web Applications with Flask

3 -Scalability and Production Readiness

4 -Monitoring and Maintenance

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تولید کننده: Udemy