A beginners guide to learn Machine Learning from scratch. Learn various algorithms and techniques using ML libraries.

What you’ll learn

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

What you’ll learn

  • Learn how to use NumPy to do fast mathematical calculations
  • Learn what is Machine Learning and Data Wrangling
  • Learn how to use scikit-learn for data-preprocessing
  • Learn different model selection and feature selections techniques
  • Learn about cluster analysis and anomaly detection
  • Learn about SVMs for classification, regression and outliers detection.
Curriculum
5 sections • 16 lectures • 6h 49m total length

Introduction to Machine Learning & Data Wrangling
  • Essential NumPy
  • Essential Pandas for Machine Learning
Linear Models, Trees & Preprocessing
Model Evaluation, Feature Selection & Pipelining
Bayes, Nearest Neighbours & Clustering
SVM, Anomalies, Imbalanced Classes, Ensemble Methods
This course includes:
  • 7 hours on-demand video
  • Full lifetime access
  • Access on mobile and TV
  • Certificate of completion

Description

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 to Machine Learning & Data Wrangling
  2. Linear Models, Trees & Preprocessing
  3. Model Evaluation, Feature Selection & Pipelining
  4. Bayes, Nearest Neighbours & Clustering
  5. SVM, Anomalies, Imbalanced Classes, Ensemble Methods

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

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