Advanced Machine Learning with Python Training Course

Saigon Tower, 29 Lê Duẩn, Bến Nghé, District 1, Ho Chi Minh City, Vietnam



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 Details :

Course Code : pythonadvml
Duration: 21 hours (usually 3 days including breaks)
Workday courses take place between 09:30 and 16:30
– Python programming experience
– An understanding of basic principles of machine learning
– Developers
– Analysts
– Data scientists
Fees : 359608316 VND(Price per participant)
Venue : Ho Chi Minh City, Saigon Tower, Vietnam

Course Outline


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


Add A Review

Please enter input field

NobleProg Limited
Training Service

Book your course now


Your enquiry submitted successfully

Enquiry Submission failed

Please enter input field(s)

Claim this course

To manage this course details kindly claim this course.