Machine Learning Foundation With Python ( Geeks For Geeks )
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Harry Potter

Harry Potter

Mar 19, 2023

Machine Learning Foundation With Python ( Geeks For Geeks )

Learn the concepts of Machine Learning and effective techniques using Python. This course includes multiple lab sessions and real-world projects from Industry experts. Recommended for beginners and working professionals.

Course Description

Find out about the concepts of Machine Learning, effective machine learning techniques from basics with Python.

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Course Outline

This course is the perfect place for beginners to comprehend the core thought of building systems that can automatically gain from data and work on the experience without being explicitly programmed. In this course, you will find out about concepts of Machine Learning, effective machine learning techniques, and gain practice executing them and inspiring them to work for yourself all in a classroom program. The course will be tutored and directed by Industry experts having active experience in ML-based industry projects. The course includes 1 major and 3 minor projects based on real-world applications with directed lab sessions.

Pre-necessities:

Ought to know the basics of any one programming language

C/C++

Java

Python

 

Recommended for:

  1. Anybody who needs to learn and assemble ML-based solutions specifically
  2. College students who are looking for preparing in Machine Learning
  3. Working Professionals who need to learn machine learning concepts.

Course Content

01

Lecture 1

Active on python.

Basic punctuation and data structures in python

Introduction to data frames, numpy, pandas and different libraries in python.

02

Lecture 2

Introduction to ML

Sorts of problems addressed by ML.

Real world scenarios where ML is applicable.

Basic Wording utilized in ML through a case study.

03

Lecture 3

Building Regression models like Linear Regression, its variants etc.

Assessing regression models, assessment metrics, cost function etc.

04

Lecture 4

Project 1 (Lab meeting)

Predicting House prices

05

Lecture 5

Introduction to classification techniques.

Logistic Regression, Decision Trees, Random Forests.

Assessing Classification Models.

06

Lecture 6

Project 2 (Lab meeting)

Inn Surveys Data Sentiment Analysis

07

Lecture 7

Clustering and Similarity techniques

Other clustering Algorithms :

 K-means Algorithm

Apriori Algorithm etc

08

Lecture 8

Project 3 (Lab meeting)

Clustering 2D points through K-Means Algorithm

09

Lecture 9

Introduction to Deep Learning

Best Practices while planning Machine Learning Solutions

Closing Remark

10

Lecture 10

Major Project

Real-time Ads Recommendation System

 

Useful Links:

 

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Harry Potter

Harry Potter

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