Python for Advanced Machine Learning Training Course

Course Code

pythonadvml

Duration

21 hours (usually 3 days including breaks)

Requirements

  • Python programming experience
  • An understanding of basic principles of machine learning

Audience

  • Developers
  • Analysts
  • Data scientists

Overview

In this instructor-led, live training, participants will learn the most relevant and cutting-edge machine learning techniques in Python as they build a series of demo applications involving image, music, text, and financial data.

By the end of this training, participants will be able to:

  • Implement machine learning algorithms and techniques for solving complex problems.
  • Apply deep learning and semi-supervised learning to applications involving image, music, text, and financial data.
  • Push Python algorithms to their maximum potential.
  • Use libraries and packages such as NumPy and Theano.

Format of the course

  • Part lecture, part discussion, exercises and heavy hands-on practice

Course Outline

Introduction

Describing the Structure of Unlabled Data

  • Unsupervised Machine Learning

Recognizing, Clustering and Generating Images, Video Sequences and Motion-capture Data

  • Deep Belief Networks (DBNs)

Reconstructing the Original Input Data from a Corrupted (Noisy) Version

  • Feature Selection and Extraction
  • Stacked Denoising Auto-encoders

Analyzing Visual Images

  • Convolutional Neural Networks

Gaining a Better Understanding of the Structure of Data

  • Semi-Supervised Learning

Understanding Text Data

  • Text Feature Extraction

Building Highly Accurate Predictive Models

  • Improving Machine Learning Results
  • Ensemble Methods

Summary and Conclusion

Testimonials

★★★★★
★★★★★

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