This is a folder 📂 that contains the codes 🧑💻, data files 🔢 and notes 📝 from the course that was sponsored by the FreeCodeCamp and taught by Kylie Ying. 👩🏫
⌨️ Introduction ⌨️ Data/Colab Introduction ⌨️ Introduction to Machine Learning ⌨️ Features ⌨️ Classification/Regression ⌨️ Training Model ⌨️ Preparing Data ⌨️ K-Nearest Neighbors ⌨️ KNN Implementation ⌨️ Naive Bayes ⌨️ Naive Bayes Implementation ⌨️ Logistic Regression ⌨️ Logistic Regression Implementation ⌨️ Support Vector Machine ⌨️ SVM Implementation ⌨️ Neural Networks ⌨️ Tensorflow ⌨️ Classification NN using Tensorflow ⌨️ Linear Regression ⌨️ Linear Regression Implementation ⌨️ Linear Regression using a Neuron ⌨️ Regression NN using Tensorflow ⌨️ K-Means Clustering ⌨️ Principal Component Analysis ⌨️ K-Means and PCA Implementations
🔗 MAGIC DATASET 🔗 BIKE DATASET** 🔗 SEEDS/WHEAT DATASET ** NOTE: For the bikes dataset, please open the downloaded csv file and remove special characters.