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Introduction to scikit learn

Apply Machine Learning in your projects through scikit-learn

2 hours+ of total content
5.0
(2 Reviews)
10 enrolled
Course Creator: Krunal PatelLast updated 11 days ago

Goals

  • Basics of ML concepts
  • Preprocessing data using scikit learn
  • Classifiers in scikit learn
  • Model evaluation using scikit learn
  • Hyperparameter tuning using scikit learn
  • Regression using scikit learn

Description

Scikit-learn is an open source machine learning library that supports supervised and unsupervised learning. Scikit-Learn is characterized by a clean, uniform, and streamlined API. It also provides various tools for model fitting, data preprocessing, model selection and evaluation, and many other built-in machine learning algorithms and models. In this course, I provide a basic introduction to scikit learn and machine learning.

You do not need to have a background in machine learning. However, knowledge of python is required for this course.

By the end of this course, you should be able to apply basic ML models in your application using scikit-learn.

Course Structure

28 lectures 02:42:24 total duration

  Introduction (Watch video)
02:51
  Introduction to machine learning 
09:56
  Data preprocessing (Watch video)
18:53
  Process_data 
05:00
  Process_data_2 
05:00
  Quiz Question 
01:00
  Quiz Question 
01:00

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May 23, 2023
Sci Kit Learn

Your Course Instructor

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Krunal Patel

Never stop learning.

I graduated from BITS Pilani Goa Campus in 2015 with B. E. (Hons.) Computer Science and M. Sc. (Hons.) Mathematics. After graduation, I worked with Google from 2015 to 2020 with operations research team. With the operations research team I worked as a developer of Google OR-Tools. I Left Google in 2020 to start my PhD under the supervision of Prof. Andrea Lodi and Prof. Guy Desaulniers in applied mathematics. My research interests: Discrete optimization Column Generation Machine Learning.

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