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Learn Machine Learning Like a GENIUS and Not Waste Time ######################################### I just started my own Patreon, in case you want to support! Patreon Link: https://www.patreon.com/c/InfiniteCodes ######################################### You won’t learn Machine Learning in 3 months. I don’t know how long it will take you but here I am sharing everything I know to get you started and make it as fast as possible. Also Watch: All Machine Learning algorithms explained in 17 min https://youtu.be/E0Hmnixke2g The Math that make Machine Learning easy (and how you can learn it) https://youtu.be/wOTFGRSUQ6Q 15 Machine Learning Lessons I Wish I Knew Earlier https://youtu.be/espQDESe07w Machine Learning Playlist: https://www.youtube.com/watch?v=wOTFGRSUQ6Q&list=PLbdTl8vSSyUDAvDPc1r3j9itciu_kb5vG&ab_channel=InfiniteCodes Git/Github Playlist: https://www.youtube.com/watch?v=ZFFtMyOFPe8&list=PLbdTl8vSSyUBJg6PI9AqfJBw8U0y9J3kY&ab_channel=InfiniteCodes 👇🏻 Links Resources I mention in the Video👇🏻 === Python === My Python for beginners playlist: https://youtube.com/playlist?list=PLbdTl8vSSyUAJid3yaBjqcMrvLwhcM6vf&si=hfFpa4SPgVlNZ9b9 Other tutorials: Official Course: https://docs.python.org/3/tutorial/index.html W3 schools: https://www.w3schools.com/python/ Uni of Helsinki MOOC: https://programming-24.mooc.fi/ Khan Academy: https://www.khanacademy.org/computing/intro-to-python-fundamentals Or simply type “Python tutorial” into Google :-) === Math === Stats & Probability: https://www.khanacademy.org/math/statistics-probability https://www.edx.org/learn/probability/harvard-university-introduction-to-probability Linear Algebra: https://www.khanacademy.org/math/linear-algebra https://www.edx.org/learn/linear-algebra/the-university-of-texas-at-austin-linear-algebra-foundations-to-frontiers 3Blue1brown (neat visuals) https://youtu.be/fNk_zzaMoSs?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab Calculus: https://www.khanacademy.org/math/differential-calculus 3Blue1Brown (amazing visuals!) https://youtu.be/WUvTyaaNkzM?si=5A_P-RlD5ICvDeQq === Data Tools === Jupyter: https://jupyter.org/ Numpy: https://numpy.org/doc/stable/user/quickstart.html Pandas: https://pandas.pydata.org/docs/user_guide/10min.html Matplotlib: https://matplotlib.org/stable/tutorials/index.html === ML Theory === ISL (free PDF) https://www.statlearning.com/ ISL Python Playlist: https://www.youtube.com/playlist?list=PLoROMvodv4rPP6braWoRt5UCXYZ71GZIQ Coursera ML introduction: https://www.coursera.org/specializations/machine-learning-introduction#courses === ML tools === SK Learn: https://scikit-learn.org/stable/tutorial/basic/tutorial.html SK Learn algorithm Cheat Sheet: https://scikit-learn.org/stable/tutorial/machine_learning_map/ === Neural Networks / Deep Learning === Coursera: https://www.coursera.org/specializations/deep-learning?irclickid=x-U2gpTSJxyLTxPwUx0Mo3EoUkDXeu01jUFXWo0&irgwc=1#courses 3Blue1Brown (amazing visuals!) https://youtu.be/aircAruvnKk?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi Andrej Kaparthy https://www.youtube.com/playlist?list=PLAqhIrjkxbuWI23v9cThsA9GvCAUhRvKZ Hugging Face NLP course: https://huggingface.co/learn/nlp-course/chapter1/1 Keras https://keras.io/getting_started/ === Real Projects === https://www.kaggle.com/ https://github.com/ ================== Timestamps ================ 00:00 - Intro 00:40 - Why learn Machine Learning & Data Science 01:11 - How to learn? 03:25 - Where to start? (Jupyter, Python, Pandas) 05:25 - Your first Data Analysis Project 06:32 - Essential Math for Machine Learning (Stats, Linear Algebra, Calculus) 08:53 - The Core Machine Learning Concepts & Algorithms (From Regression to Deep Learning) 10:16 - Scikit Learn 11:37 - Your first Machine Learning Project 13:24 - Collaborate & Share 13:59 - Advanced Topics 14:22 - Do’s and Don'ts Key Highlights & Overview: Understanding <strong>Infinite Codes</strong> requires clear step-by-step guidance and practical hands-on visual demonstrations. Follow along with top-rated video tutorials from industry experts today on <strong>TutorTube</strong>.