Machine Learning for Everybody – Full Course

>> YOUR LINK HERE: ___ http://youtube.com/watch?v=i_LwzRVP7bg

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: / ycubed • ⭐️ Code and Resources ⭐️ • 🔗 Supervised learning (classification/MAGIC): https://colab.research.google.com/dri... • 🔗 Supervised learning (regression/bikes): https://colab.research.google.com/dri... • 🔗 Unsupervised learning (seeds): https://colab.research.google.com/dri... • 🔗 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/datase... • 🔗 Bikes dataset: https://archive.ics.uci.edu/ml/datase... • 🔗 Seeds/wheat dataset: https://archive.ics.uci.edu/ml/datase... • 🏗 Google provided a grant to make this course possible. • ❤️ Support for this channel comes from our friends at Scrimba – the coding platform that's reinvented interactive learning: https://scrimba.com/freecodecamp • ⭐️ 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.org • Read hundreds of articles on programming: https://freecodecamp.org/news

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