class_01
: Introduction to Machine Learning, Python Basics
class_02
: Numpy, Matplotlib, Statistics
class_03
: Pandas, KNN, KNN on MNIST
class_04
: OpenCV, Face Detection using Haar Cascade, Face Recognition
class_05
: KMeans, Dominant Color Extraction and Image Segmentation
class_06
: Decision Trees, Random Forest
class_07
: Principal Component Analysis (PCA)
class_08
: [Uni, Multi]Variate Linear Regression
class_09
: Logistic Regression
class_10
: Neural Network Theory
class_11
: NN from scratch, Keras Sequential on MNIST
class_12
: Convolutional Neural Networks (CNN)
class_13
: [Stacked, Convolutional] AutoEncoders, Keras Functional API
class_14
: NLTK, Web Scraping
class_15
: Naive Bayes, Markov Chains (Text Generation)
class_16
: Word2Vec with Gensim, Train Word Embeddings (bi-gram context)
class_17
: RNN, LSTM, GRU
class_18
: Transfer Learning, Deep Dream, Neural Art
class_19
: Seq2Seq, LSTM Applications
class_20
: Genetic Algorithms, Intro to RL
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