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Machine Learning Projects for Beginners: Work on 10 Projects

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Machine Learning Projects for Beginners: Work on 10 Projects, available at $69.99, has an average rating of 4.68, with 59 lectures, based on 188 reviews, and has 1346 subscribers.

You will learn about Complete understanding of Machine Learning Project flow Machine Learning Practical Applications Machine Learning for Regression Problems Machine Learning for Classification Problems Clustering with Machine Learning NLP with Machine Learning Improving the performance of a machine learning model Predicting a single observation This course is ideal for individuals who are Anyone who wants to learn Machine Learning project building or Students and Professionals who want to start a career in Data Science and Machine Learning It is particularly useful for Anyone who wants to learn Machine Learning project building or Students and Professionals who want to start a career in Data Science and Machine Learning.

Enroll now: Machine Learning Projects for Beginners: Work on 10 Projects

Summary

Title: Machine Learning Projects for Beginners: Work on 10 Projects

Price: $69.99

Average Rating: 4.68

Number of Lectures: 59

Number of Published Lectures: 59

Number of Curriculum Items: 59

Number of Published Curriculum Objects: 59

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will Learn

  • Complete understanding of Machine Learning Project flow
  • Machine Learning Practical Applications
  • Machine Learning for Regression Problems
  • Machine Learning for Classification Problems
  • Clustering with Machine Learning
  • NLP with Machine Learning
  • Improving the performance of a machine learning model
  • Predicting a single observation

Who Should Attend

  • Anyone who wants to learn Machine Learning project building
  • Students and Professionals who want to start a career in Data Science and Machine Learning

Target Audiences

  • Anyone who wants to learn Machine Learning project building
  • Students and Professionals who want to start a career in Data Science and Machine Learning

Machine Learning and Data Science are one of the hottest tech fields now a days ! There are plenty of career opportunities in these fields. They have applications in almost every field, like transportation, Finance, Banking, Healthcare, Defense, Entertainment, etc.

Most of the students and professionals learn Data Science but specifically they are facing difficulties in building the projects, and to solve this problem i have created this course.

In this course you will learn to build Machine Learning projects from the scratch, here you will build each and every project from very beginning.

You will work on a variety of Machine Learning projects,

1) Regression

2) Classification

3) Clustering

4) Natural Language Processing

You will do below main steps in each project,

1) Data Preprocessing

2) Data Exploration

3) Model Building

4) Finalizing the Machine Learning Model

5) Hyper-Parameter tuning

6) Predicting a single observation

List of the Projects that you will work on,

Project 1: Breast Cancer Detection

Project 2: Customer churn rate prediction

Project 3: Medical insurance premium prediction

Project 4: House price prediction

Project 5: E signing of customers based on financial data

Project 6: Credit card fraud detection

Project 7: Employee Attrition Prediction

Project 8:  Customer Segmentation

Project 9: Used Car Price Prediction

Project 10:Restaurant Reviews Classification

This course is for the students and the professionals to gain complete understanding of Machine Learning project building. Basic knowledge of machine learning is machine learning and programming is an added advantage.

Course Curriculum

Chapter 1: Introduction

Lecture 1: Welcome to the Course !

Lecture 2: Updates on Udemy Reviews

Lecture 3: Course FAQ's

Lecture 4: Colab Notebooks

Chapter 2: Project 1: Breast Cancer Detection

Lecture 1: Business Problem

Lecture 2: Data Preprocessing: Part 1

Lecture 3: Data Preprocessing: Part 2

Lecture 4: Logistic Regression

Lecture 5: Random Forest Classifier

Lecture 6: Hyperparameter Tuning using Randomized search

Lecture 7: Predicting a Single Observation

Chapter 3: Project 2: Customer churn rate prediction

Lecture 1: Business Problem

Lecture 2: Data Preprocessing part 1

Lecture 3: Data Preprocessing part 2

Lecture 4: Logistic Regression

Lecture 5: Random Forest Classifier

Lecture 6: XGBoost Classifier

Lecture 7: Hyperparameter Tuning using Randomized Search

Lecture 8: Predicting a Single Observation

Chapter 4: Project 3: Medical insurance premium prediction

Lecture 1: Business Problem

Lecture 2: Data Preprocessing: Part 1

Lecture 3: Data Preprocessing: Part 2

Lecture 4: Building and Finalizing the model

Lecture 5: Predicting a single observation

Chapter 5: Project 4: House price prediction

Lecture 1: Business Problem

Lecture 2: Data Preprocessing: Part 1

Lecture 3: Data Preprocessing: Part 2

Lecture 4: Building and Finalizing the model

Lecture 5: Hyperparameter Tuning using Randomized Search

Chapter 6: Project 5: E signing of customers based on financial data

Lecture 1: Business Problem

Lecture 2: Data Preprocessing: Part 1

Lecture 3: Data Preprocessing: Part 2

Lecture 4: Building and Finalizing the model

Lecture 5: Hyperparameter Tuning using Randomized Search

Lecture 6: Predicting a single observation

Chapter 7: Project 6: Credit card fraud detection

Lecture 1: Business Problem

Lecture 2: Data Preprocessing: Part 1

Lecture 3: Data Preprocessing: Part 2

Lecture 4: Building and Finalizing the model

Lecture 5: Predicting a single observation

Chapter 8: Project 7: Employee Attrition Prediction

Lecture 1: Business Problem

Lecture 2: Data Preprocessing: Part 1

Lecture 3: Data Preprocessing: Part 2

Lecture 4: Building and Finalizing the model

Lecture 5: Hyperparameter Tuning using Randomized Search

Lecture 6: Predicting a single observation

Chapter 9: Project 8: Customer Segmentation

Lecture 1: Business Problem

Lecture 2: Data Preprocessing

Lecture 3: Building the model and predicting results

Chapter 10: Project 9: Used Car Price Prediction

Lecture 1: Business Problem

Lecture 2: Data Preprocessing Part 1

Lecture 3: Data Preprocessing Part 2

Lecture 4: Building and finalizing the Model

Lecture 5: Hyper-Parameter tuning and predicting the results

Chapter 11: Project 10: Restaurant Reviews Classification

Lecture 1: Business Problem

Lecture 2: Data Preprocessing Part 1

Lecture 3: Data Preprocessing Part 2

Lecture 4: Data Preprocessing Part 3

Lecture 5: Building and Finalizing the Model

Instructors

Rating Distribution

  • 1 stars: 4 votes
  • 2 stars: 5 votes
  • 3 stars: 18 votes
  • 4 stars: 54 votes
  • 5 stars: 107 votes

Frequently Asked Questions


How long do I have access to the course materials?


You can view and review the lecture materials indefinitely, like an on-demand channel.


Can I take my courses with me wherever I go?


Definitely! If you have an internet connection, courses on Udemy are available on any device at any time. If you don’t have an internet connection, some instructors also let their students download course lectures. That’s up to the instructor though, so make sure you get on their good side!

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