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         Recommender Systems with Python培訓

Introduction

What is AI

Computational Psychology
Computational Philosophy
Machine Learning

Computational learning theory
Computer algorithms for computational experience
Deep Learning

Artificial neural networks
Deep learning vs. machine learning
Preparing the Development Environment

Setting up Python libraries and Apache Spark
Recommendation Systems

Building a recommender engine frameworks
Testing and evaluating algorithms
Collabrative Filtering

Working with user-based and content-based filtering
Working with neighbor-based filtering
Using RBMs
Matrix Factorization

Using and extending PCA
Running and improving SVD
Working with Keras and deep learning neural networks
Scaling with Spark

Using RDDs and dataframes
Setting up clusters on AWS / EC2
Scaling Amazon DSSTNE and SageMaker
Summary and Conclusion