5 Real-Time Use Cases using Machine Learning



Learn Machine Learning and Deep Learning with 5 Real World projects

What you will learn

Learn how to program in Python using the latest Python 3

Learn to perform Classification and Regression modelling

Learn to use the popular library Scikit-learn in your projects

Real life case studies and projects to understand how things are done in the real world

Explore large datasets and wrangle data using Pandas

Build artificial neural networks with Tensorflow and Keras

Understand the intuition behind Artificial Neural Networks

Deep Learning, Transfer Learning and Neural Networks using the latest Tensorflow 2.0

Make robust Machine Learning models

How to improve your Machine Learning Models

Implement Machine Learning algorithms

Description

Are you ready to start your path to becoming a Data Scientist or ML Engineer?

This comprehensive course will be your guide to learning how to use the power of Python to analyze data, create beautiful visualizations, and use powerful machine learning algorithms!

Data Scientist has been ranked the number one job on Glassdoor and the average salary of a data scientist is over $120,000 in the United States according to Indeed! Data Science is a rewarding career that allows you to solve some of the world’s most interesting problems!

This course is designed for both beginners with some programming experience or experienced developers looking to make the jump to Data Science!

This comprehensive course is comparable to other Data Science bootcamps that usually cost thousands of dollars, but now you can learn all that information at a fraction of the cost! We will take you through 5 real-world projects and you can use those projects in your resume as well. The videos are designed in such a way that we will cover all the prerequisites and you just need to understand the flow.


We’ll teach you how to create awesome Machine Learning and Deep Learning Projects with Python! Here a just a few of the topics we will be learning:

  1. Programming with Python

  2. NumPy with Python

  3. Using pandas Data Frames to solve complex tasks

  4. Use pandas to handle Excel Files

  5. Use ML models from Scikit-learn

  6. Use different NLP techniques

  7. Make Neural Network Architecture

Moreover, the course is packed with quizzes that will help you check your knowledge while learning to build the projects.

And as a bonus, this course includes Python code templates which you can download and use as your own projects.

English
language

Content

Introduction

Course Introduction

Project 01 : Chatbot

Test Your Prior Knowledge
Introduction
Exploring the Data
Preprocessing the Text Data
Creating and Training the model
Making Predictions using Chatbot
Conclusion
Check your Understanding

Project 02 : Fake News Classification

Introduction
Preprocessing the Data
Walkthrough the Data
Importing Dataset
Training and Testing the model
Conclusion
Check your Understanding

Project 03 : Customer Churn Prediction

Introduction
Importing Dataset
Gaining Insights from the Data
Manipulating the Data
Training and Exporting the model
Conclusion
Check your Understanding

Project 4 : Car Price Prediction

Introduction
Dataset and Libraries
Importing Dataset
Encoding and Splitting the Data
Training and Exporting the model
Conclusion
Check your Understanding

Project 5 : Fashion Product Classifier

Introduction
About the Dataset
Downloading the Dataset in Colab
Preparing the Data
Preparing ImageDataGenerator
Initializing the Neural Network
Training the Neural Network
Making Prediction
Conclusion
Check your Understanding

Check Today's 30+ Free Courses on Telegram!

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