Machine Learning for Everybody – Full Course

Learn Machine Learning in a way that is accessible to absolute beginners. You will learn the basics of Machine Learning and how to use TensorFlow to implement many different concepts.✏ Kylie Ying developed this course. Check out her channel: https://www.youtube.com/c/YCubed⭐ Code and Resources ⭐🔗 Supervised learning (classification/MAGIC): https://colab.research.google.....com/drive/16w3TDn_tA Supervised learning (regression/bikes): https://colab.research.google.....com/drive/1m3oQ9b0oY Unsupervised learning (seeds): https://colab.research.google.....com/drive/1zw_6ZnFPC Dataets (add a note that for the bikes dataset, they may have to open the downloaded csv file and remove special characters)🔗 MAGIC dataset: https://archive.ics.uci.edu/ml..../datasets/MAGIC+Gamm Bikes dataset: https://archive.ics.uci.edu/ml..../datasets/Seoul+Bike Seeds/wheat dataset: https://archive.ics.uci.edu/ml/datasets/seeds🏗 Google provided a grant to make this course possible. ⭐ Contents ⭐⌨ (0:00:00) Intro⌨ (0:00:58) Data/Colab Intro⌨ (0:08:45) Intro to Machine Learning⌨ (0:12:26) Features⌨ (0:17:23) Classification/Regression⌨ (0:19:57) Training Model⌨ (0:30:57) Preparing Data⌨ (0:44:43) K-Nearest Neighbors⌨ (0:52:42) KNN Implementation⌨ (1:08:43) Naive Bayes⌨ (1:17:30) Naive Bayes Implementation⌨ (1:19:22) Logistic Regression⌨ (1:27:56) Log Regression Implementation⌨ (1:29:13) Support Vector Machine⌨ (1:37:54) SVM Implementation⌨ (1:39:44) Neural Networks⌨ (1:47:57) Tensorflow⌨ (1:49:50) Classification NN using Tensorflow⌨ (2:10:12) Linear Regression⌨ (2:34:54) Lin Regression Implementation⌨ (2:57:44) Lin Regression using a Neuron⌨ (3:00:15) Regression NN using Tensorflow⌨ (3:13:13) K-Means Clustering⌨ (3:23:46) Principal Component Analysis⌨ (3:33:54) K-Means and PCA Implementations🎉 Thanks to our Champion and Sponsor supporters:👾 Raymond Odero👾 Agustín Kussrow👾 aldo ferretti👾 Otis Morgan👾 DeezMaster--Learn to code for free and get a developer job: https://www.freecodecamp.orgRead hundreds of articles on programming: https://freecodecamp.org/news