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 ⭐️
ð??? Supervised learning (classification/MAGIC): https://colab.research.google.com/drive/16w3TDn_tAku17mum98EWTmjaLHAJcsk0?usp=sharing
ð??? Supervised learning (regression/bikes): https://colab.research.google.com/drive/1m3oQ9b0oYOT-DXEy0JCdgWPLGllHMb4V?usp=sharing
ð??? Unsupervised learning (seeds): https://colab.research.google.com/drive/1zw_6ZnFPCCh6mWDAd_VBMZB4VkC3ys2q?usp=sharing
ð??? Dataets (add a note that for the bikes dataset, they may have to open the downloaded csv file and remove special characters)
ð??? MAGIC dataset: https://archive.ics.uci.edu/ml/datasets/MAGIC+Gamma+Telescope
ð??? Bikes dataset: https://archive.ics.uci.edu/ml/datasets/Seoul+Bike+Sharing+Demand
ð??? Seeds/wheat dataset: https://archive.ics.uci.edu/ml/datasets/seeds

ð?? 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

ð??? Thanks to our Champion and Sponsor supporters:
ð??¾ Raymond Odero
ð??¾ Agustín Kussrow
ð??¾ aldo ferretti
ð??¾ Otis Morgan
ð??¾ DeezMaster

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