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AI & Machine Learning

Deep Learning with PyTorch

A three-day path from data handling to neural networks in PyTorch.

3 daysIntermediate12 modules
Overview

About this course

A three-day path from data handling to neural networks in PyTorch. You will prepare data with NumPy and pandas, learn core machine learning theory and evaluation, then build and train deep learning models for tasks such as image classification.

What you'll learn

What you'll learn

  • Learn how to use NumPy to format data into arrays
  • Use pandas for data manipulation and cleaning
  • Learn classic machine learning theory principals
  • Use PyTorch Deep Learning Library for image classification
  • Use PyTorch with Recurrent Neural Networks for Sequence Time Series Data
  • Create state of the art Deep Learning models to work with tabular data
Curriculum

Curriculum

12 modules
1NumPy
2Pandas
3Machine Learning Theory
4Test/Train/Validation Data Splits
5Model Evaluation - Regression and Classification Tasks
6Unsupervised Learning Tasks
7Tensors with PyTorch
  • Perceptrons
  • Networks
  • Activation Functions
  • Cost/Loss Functions
  • Backpropagation
9Gradients
10Artificial Neural Networks
11Convolutional Neural Networks
12Recurrent Neural Networks
Who it's for

Who it's for

Analysts, developers and engineers with basic Python who want to move into deep learning.

Before you start

  • Introduction to Python and Python for Data Science ; Python for Machine Learning recommended

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