Coding Ninjas

1. Data Science & Machine Learning Complete Course

Introduction To Python

Conditions and Loops

Patterns

More on Loops

Functions

Tuples, Dictionary And Sets

Object Oriented Programming Systems(OOPs)

Pandas

Plotting Graphs

Structured Query Language(SQL) - Basic

Structured Query Language(SQL) - Advance

Indexing And SQLite

Application Programming Interfaces(APIs) - II

Web Scraping - BeautifulSoup

Web Scraping - Selenium

Web Scraping : Advanced Selenium

Statistics

Descriptive Statistics

Introduction to Machine Learning

Linear Regression

MultiVariable Regression And Gradient Descent

Feature Scaling

Logistic Regression

Classification Measures

Decision Trees - I

Decision Trees - II

Random Forests

Naive Bayes

Project: Text Classification

K-Nearest Neighbours(K-NN)

Support Vector Machine(SVM)

Principal Component Analysis(PCA) - I

Principal Component Analysis(PCA) - II

Natural Language Processing(NLP) - I

Natural Language Processing(NLP) - II

Neural Networks - I

Neural Networks - II

Tensor Flow

Keras

Convolutional Neural Network(CNN) - I

Convolutional Neural Network(CNN) - II

Recurrent Neural Network(RNN)

Long Short-Term Memory(LSTM)

Unsupervised Learning - I

Unsupervised Learning - II

Git

Topics

Intro to unsupervised learning

Introduction to clustering

Using KMeans for Flat Clustering

KMeans Algorithm

Using KMeans from SKLearn

Starter Code for KMeans

Implementing Fit & Predict Functions

Implementing KMeans Class

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