Data Science və Maşın Öyrənməsi

Introduction to Programming

Conditional Statements

Strings

Loops

Functions

Data Structures & Algorithms (for Data Science)

Comparative Analysis of Data Structures

Pandas for Data Analysis/Data Cleaning/Data Processing

NumPy

Data Visualization: Plotly, Matplotlib, Seaborn

OOP

Sample & Population differences, Mean, Median, Mode, Variance, Deviation

Philosophy of Randomness, Random Variables

Covariance and Correlation

Quantiles, Outlier Detection and Exclusion

The Application and Moral of Standardization and Normalization of the Data

Distributions: Normal Distribution, Binomial Distribution

P value, Hypothesis testing

Supervised vs Unsupervised Learning

Machine Learning Model Preparation Stages

Regression Analysis: Linear Regression

Gradient Descent in Linear Regression

Logistic Regression

Regularization

Variance vs Bias

Error Metrics

K-Means

Decision Tree

PCA

Anomaly Detection

Recommender System

Neural Networks

Large Scale Machine Learning

Convolutional Neural Networks

Recurrent Neural Networks

Timeseries Analysis

Data Cleaning and Preprocessing Procedures in Natural Language Processing / Understanding / Generation