This course is a practical and hands-on introduction to Machine Learning with Python and Scikit-Learn for beginners with basic knowledge of Python and statistics.
It is designed and taught by Aakash N S, CEO and co-founder of Jovian. Check out their YouTube channel here: youtube.com/@jovianhq
We'll start with the basics of machine learning by exploring models like linear & logistic regression and then move on to tree-based models like decision trees, random forests, and gradient-boosting machines. We'll also discuss best practices for approaching and managing machine learning projects and build a state-of-the-art machine learning model for a real-world dataset from scratch. We'll also look at unsupervised learning & recommendations briefly and walk through the process of deploying a machine-learning model to the cloud using the Flask web framework.
By the end of this course, you'll be able to confidently build, train, and deploy machine learning models in the real world. To get the most out of this course, follow along & type out all the code yourself, and apply the techniques covered here to other real-world datasets & competitions that you can find on platforms like Kaggle.
⭐️ Topics & Notebooks ⭐️
⌨️ (00:00:00) Introduction
⌨️ (00:00:25) Lesson 1 - Linear Regression and Gradient Descent
🔗 jovian.ai/aakashns/python-sklearn-linear-regression
⌨️ (02:17:30) Lesson 2 - Logistic Regression for Classification
🔗 jovian.ai/aakashns/python-sklearn-logistic-regression
⌨️ (04:53:26) Lesson 3 - Decision Trees and Random Forests
🔗 jovian.ai/aakashns/sklearn-decision-trees-random-forests
⌨️ (07:25:29) Lesson 4 - How to Approach Machine Learning Projects
🔗 jovian.com/aakashns/how-to-approach-ml-problems
⌨️ (10:06:13) Lesson 5 - Gradient Boosting Machines with XGBoost
🔗 jovian.ai/aakashns/python-gradient-boosting-machines
⌨️ (12:20:57) Lesson 6 - Unsupervised Learning using Scikit-Learn
🔗 jovian.ai/aakashns/sklearn-unsupervised-learning , jovian.ai/aakashns/movielens-fastai
⌨️ (13:53:18) Lesson 7 - Machine Learning Project from Scratch
🔗 jovian.com/aakashns/nyc-taxi-fare-prediction-filled , jovian.com/aakashns/nyc-taxi-fare-prediction-blank
⌨️ (16:45:47) Lesson 8 - Deploying a Machine Learning Project with Flask
🔗 jovian.com/biraj/deploying-a-machine-learning-model
🎉 Thanks to our Champion and Sponsor supporters:
👾 davthecoder
👾 jedi-or-sith
👾 南宮千影
👾 Agustín Kussrow
👾 Nattira Maneerat
👾 Heather Wcislo
👾 Serhiy Kalinets
👾 Justin Hual
👾 Otis Morgan
👾 Oscar Rahnama
--
Learn to code for free and get a developer job: freecodecamp.org
Read hundreds of articles on programming: freecodecamp.org/news
- Machine Learning with Python and Scikit-Learn – Full Course ( Download)
- Scikit-learn Crash Course - Machine Learning Library for Python ( Download)
- Scikit-Learn Course - Machine Learning in Python Tutorial ( Download)
- Real-World Python Machine Learning Tutorial w/ Scikit Learn (sklearn basics, NLP, classifiers, etc) ( Download)
- Machine Learning for Everybody – Full Course ( Download)
- How I’d learn ML in 2024 (if I could start over) ( Download)
- Python Machine Learning Tutorial (Data Science) ( Download)
- Is this still the best book on Machine Learning ( Download)
- Working Of For Loop in Python I Data Science I Prwatech ( Download)
- Scikit-Learn Tutorial | Machine Learning With Scikit-Learn | Sklearn | Python Tutorial | Simplilearn ( Download)
- Machine Learning in 2024 – Beginner's Course ( Download)
- I can't STOP reading these Machine Learning Books! ( Download)
- Learning Scikit-Learn ( Download)
- Building a Machine Learning Pipeline with Python and Scikit-Learn | Step-by-Step Tutorial ( Download)
- Scikit Learn Tutorial | Machine Learning with Python | Python for Data Science Training | Edureka ( Download)