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12 Real-World Case Studies For Machine Learning

person icon Akshay Deep Lamba

4.1

12 Real-World Case Studies For Machine Learning

Learn Machine Learning by working with real-world case studies. Become an industry grandmaster on Kaggle.

updated on icon Updated on Apr, 2024

language icon Language - English

person icon Akshay Deep Lamba

English [CC]

category icon Development,Data Science and AI ML,Artificial Intelligence

Lectures -102

Duration -11 hours

4.1

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Course Description

Machine Learning course by Tutorials Point provides real-world case studies for your better understanding. You can grasp the subject fundamentally from numerous courses and even get familiar with algorithm development and Machine Learning in theory. This course will cover the applications and case studies from the industry.

12 Real-World Case Studies For Machine Learning Overview

This course will assist you in bridging the knowledge gap between those who understand machine learning and those who can really put it to use in the real world. Understanding machine learning and using it in practice are two completely different things.

You will learn how to work with large, complicated data sets and use machine-learning approaches to produce effective outcomes in this course. These case studies can be included in your Portfolio, which can improve your resume as well.

The Case Studies that are covered in this course:

Regression Case Studies

  • Retail Store Sales Prediction

  • Restaurant Sales Prediction

  • Inventory Prediction for Optimum Inventory Management

  • Tube Assembly Pricing for Optimizing the Manufacturing Facility

  • Coal Production Estimation

  • Sports Player Salary Prediction

Classification Case Studies

  • Diabetes Prediction for Preventive Care

  • Telecom Network Disruptions Prediction for Planning Preventive Maintenance

  • Breast Cancer Prediction for Preventive Care

  • Credit Card Fraud Detection

  • Heart Diseases Prediction for Preventive Care

  • Predict whether a Customer Shall Sign a Loan or Not

Goals

What will you learn in this course:

  • Get experience with the Machine Learning application

  • Visualize and conduct exploratory data analysis on difficult real-world Datasets Using Mayplotlib, Seaborn, and Plotly.

  • Add industry case studies to your portfolio

  • Learn Feature Engineering for large and complicated data collections

  • Use large and complicated data sets to learn feature selection

  • Enhance and fine-tune hyperparameters

  • Get knowledge of advanced algorithms such as XGBoost, CatBoost, LightGBM, etc.

  • Discover regularisation

  • Recognize and experience the complexity of Machine Learning problems in the real world.

  • Improve your ability to handle problem statements with Machine Learning.

Prerequisites

What are the prerequisites for this course?

  • Basics of Machine Learning

  • Python Programming

  • Jupyter Notebook

12 Real-World Case Studies For Machine Learning

Curriculum

Check out the detailed breakdown of what’s inside the course

Introduction
2 Lectures
  • play icon Introduction 03:37 03:37
  • play icon Data and NoteBook Resources
REGRESSION CASE STUDY : Retail Store Sales Prediction
7 Lectures
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CLASSIFICATION CASE STUDY : Telstra Telecom Network Disruptions Challenge
10 Lectures
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REGRESSION CASE STUDY : Restaurant Sales Prediction
9 Lectures
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CLASSIFICATION CASE STUDY : Credit Card Fraud Detection
7 Lectures
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REGRESSION CASE STUDY : Inventory Prediction
7 Lectures
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CLASSIFICATION CASE STUDY : Diabetes Prediction
8 Lectures
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REGRESSION CASE STUDY : Caterpillar Tube Assembly Pricing
9 Lectures
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CLASSIFICATION CASE STUDY : Breast Cancer Prediction
7 Lectures
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REGRESSION CASE STUDY : Coal Production Estimation
7 Lectures
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CLASSIFICATION CASE STUDY : Heart Diseases Prediction
9 Lectures
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CLASSIFICATION CASE STUDY : Predict whether a Customer Shall Sign a Loan or Not
7 Lectures
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REGRESSION CASE STUDY : Player Salary Prediction
11 Lectures
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Conclusion
1 Lectures
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Instructor Details

Akshay Deep Lamba

Akshay Deep Lamba

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M

Mohan Aravind

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Awesome Case Study and Explanation. I feel like I got what i wanted

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