Step by Step Guide to Machine Learning

A beginners guide to learn Machine Learning including Hands on from scratch.

Expected learning & outcomes

  • Learn how to use NumPy to do fast mathematical calculations in machine learning.
  • Learn what is Machine Learning and Data Wrangling in machine learning.
  • Learn how to use scikit-learn for data-preprocessing in machine learning.
  • Learn different model selection and feature selections techniques in machine learning.
  • Learn about cluster analysis and anomaly detection in machine learning.
  • Learn about SVMs for classification, regression and outliers detection in machine learning.

Course details

Topic: Machine Learning

Duration: 7 hours

Level: Any Level

Certification: Available

Created by: EdYoda Digital University

Language: English

Provider: Udemy

About this course

If you are looking to start your career in machine learning then this is the course for you.

This is a course designed in such a way that you will learn all the concepts of machine learning right from basic to advanced levels.

This course has 5 parts as given below:

  1. Introduction & Data Wrangling in machine learning

  2. Linear Models, Trees & Preprocessing in machine learning

  3. Model Evaluation, Feature Selection & Pipelining in machine learning

  4. Bayes, Nearest Neighbours & Clustering in machine learning

  5. SVM, Anomalies, Imbalanced Classes, Ensemble Methods in machine learning

For the code explained in each lecture, you can find a GitHub link in the resources section.

Who this course is for:

  • Beginners who want to become a data scientist
  • Software developers who want to learn machine learning from scratch
  • Python developers who are interested to learn machine learning
  • Professionals who want to start their career in Machine Leaning
2020-09-19 10:09:11+00:00
4.2 (539 ratings)