PyTorch Basics for Machine Learning

PyTorch Basics for Machine Learning

Course
en
English
20 h
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Source
  • From www.edx.org
Conditions
  • Self-paced
  • Free Access
  • Fee-based Certificate
More info
  • 5 Sequences
  • Introductive Level

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Course details

Syllabus

Module 1

  • Tensors 1D
  • Two-Dimensional Tensors
  • Derivatives In PyTorch
  • Dataset

Module 2

  • Prediction Linear Regression
  • Training Linear Regression
  • Loss
  • Gradient Descent
  • Cost
  • Training PyTorch

Module 3

  • Gradient Descent
  • Mini-Batch Gradient Descent
  • Optimization in PyTorch
  • Training and Validation
  • Early stopping

Module 4

  • Multiple Linear Regression Prediction
  • Multiple Linear Regression Training
  • Linear regression multiple outputs
  • Multiple Output Linear Regression Training

Module 5

Final project

Prerequisite

None.

Instructors

Joseph Santarcangelo
PhD., Data Scientist
IBM

Platform

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