AI Features

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All LessonsFree Lessons (13)

What you'll learn from this course

Data Manipulation with NumPy

Introduction NumPy Arrays NumPy Basics Math Random Indexing Filtering Statistics Aggregation Saving Data Quiz

Data Analysis with pandas

Introduction Series DataFrame Combining Indexing File I/O Grouping Features Filtering Sorting Metrics Plotting To NumPy Pandas Cheat Sheet Quiz

Data Preprocessing with scikit-learn

Introduction Standardizing Data Data Range Robust Scaling Normalizing Data Data Imputation PCA Labeled Data Quiz

Data Modeling with scikit-learn

Introduction Linear Regression Ridge Regression LASSO Regression Bayesian Regression Logistic Regression Decision Trees Training and Testing Cross-Validation Applying CV to Decision Trees Evaluating Models Exhaustive Tuning Quiz

Clustering with scikit-learn

Cosine Similarity

Nearest Neighbors

K-Means Clustering

Hierarchical Clustering

Mean Shift Clustering

Evaluating Clusters

Feature Clustering

Gradient Boosting with XGBoost

Introduction XGBoost Basics Cross-Validation Storing Boosters XGBoost Classifier XGBoost Regressor Feature Importance Hyperparameter Tuning Model Persistence Quiz

Deep Learning with TensorFlow

Introduction Model Initialization Logits Metrics Optimization Training Evaluation Linear Limitations Hidden Layer Multiclass Softmax Quiz

Deep Learning with Keras

Sequential Model

Model Configuration

Model Execution

Course Conclusion

Machine Learning with NumPy, pandas, scikit-learn, and More

Introduction

An overview of unsupervised learning and clustering.

We'll cover the following...

A. Unsupervised learning

In this chapter, continuing with scikit-learn, you will use ...

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