Projects using Machine Learning
- Rainfall prediction using Linear regression
- Identifying handwritten digits using Logistic Regression in PyTorch
- Kaggle Breast Cancer Wisconsin Diagnosis using Logistic Regression
- Implement Face recognition using k-NN with scikit-learn
- Credit Card Fraud Detection
- Image compression using K-means clustering
Machine Learning with Python Tutorial
In this Machine Learning with Python Tutorial, you’ll learn basic to advanced topics, including the basics of Python programming and Machine learning, Data processing, Supervised learning, Unsupervised Learning, etc. This tutorial will provide you with a solid foundation in the fundamentals of machine learning with Python.
Well, Machine Learning is a subdomain of artificial intelligence. It allows computers to learn and improve from experience without being explicitly programmed by programmers, and It is designed in such a way that allows systems to identify patterns, make predictions, and make decisions based on data. Here, Python, a versatile programming language, has become a good-to-go choice for all to start with, and it helps many machine learning enthusiasts due to Pythons simplicity, a vast collection of libraries, and a large number of applications.
So, let’s dig deep into the Python Machine Learning guide to learn more about ML.
Table of Content
- What is Machine Learning?
- Python’s Role in Machine Learning
- Setting Up Python for Machine Learning
- Introduction
- Data Processing
- Supervised learning
- Unsupervised Learning
- Projects using Machine Learning
- Applications of Machine Learning