Build powerful machine learning models to make predictions and uncover hidden patterns. Start with foundational supervised learning algorithms, including linear regression, decision trees, naive Bayes, support vector machines (SVMs), and perceptrons, then evaluate your model performance with a variety of evaluation metrics. Then, you'll advance from perceptrons to deep neural networks in order to perform supervised learning on complex data sources such as images. Finally, you'll dive into unsupervised learning methods, including clustering and dimensionality reduction for customer segmentation. For each technique, you'll start by learning the underlying math, then implement real-world models with Python libraries, including PyTorch and scikit-learn.
Introduction to Machine Learning with Pytorch
Kaggle , Amazon Web Services and Amazon via Udacity Nanodegree
Overview
Syllabus
- Introduction to Machine Learning
- Welcome to Machine learning with Pytorch
- Supervised Learning
- In this course, you'll learn about different types of supervised learning and how to use them to solve real-world problems.
- Introduction to Neural Networks with PyTorch
- Learn the fundamentals of neural networks with Python and PyTorch, and then use your new skills to create your own image classifier—an application that will first train a deep learning model on a dataset of images and then use the trained model to classify new images.
- Unsupervised Learning
- In this course, you'll learn how to apply unsupervised learning to solve real-world problems.
- Congratulations!
- Prerequisite: Python for Data Analysis
- Prerequisite: SQL for Data Analysis
- Prerequisite: Command Line Essentials
- Prerequisite: Git & Github
- Additional Material: Python for Data Visualization
- Additional Material: Statistics for Data Analysis
- Additional Material: Linear Algebra
- Career Services
Taught by
Cezanne Camacho, Mat Leonard, Luis Serrano, Dan Romuald Mbanga, Jennifer Staab, Sean Carrell, Josh Bernhard , Jay Alammar and Andrew Paster
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Reviews
4.0 rating, based on 5 Class Central reviews
4.7 rating at Udacity based on 248 ratings
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"This program so far has exceeded my expectations. First, access to mentors that readily answers questions is so valuable. When learning a new topic it is so easy to get stuck and frustrated, but when you can reach out to someone that can answer you…
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very poor content don't worth the money and the time
it even redirect you to Khan Academy Videos and YouTube videos to cover the important parts -
It is exceeding my expectations so far. My projects have been promptly reviewed and the feedbacks are extremely thorough and constructive.
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I really enjoyed the lesson as they stroke a balance of not going too technical but technically sufficient. However, there have been many bugs/mistakes on quizzes that I have made feedback over which certainly made me annoyed.
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For now, I have finished the machine learning part, which is the first part of the course. First of all, the language of expression was very explanatory, simple and well designed for teaching. Secondly, I will talk about the narrative structure of the subjects again, because explaining the subject and then asking questions or exercises about it and sharing different resources provide better learning. Third, the feedback given in the project evaluation was helpful.
