README.md

Machine-Learning

Hello, Wanna learn Ml. If yes, then read this article. It will help you to know what is ML? Where to start? How to Start?

➡️ Article

Hope you have read above article Now I will continue.

Steps to Master ML

📚 Python Introduction

Python basics

📚 Libraries

1. Numpy
2. Pandas
3. Matplotlib

📚 EDA

Exploratory Data Analysis (EDA) is the process of visualizing and analyzing data to extract insights from it. In other words, EDA is the process of summarizing important characteristics of data in order to gain better understanding of the dataset. Do EDA before applying any ML Models. For more information see this examples

➡️ EDA

Before applying any model one should first split dataset

📚 Splitting dataset into training set and testing set

Used for splitting the dataset into the training set and the testing set. train_test_split divide the datasets into two parts for testing and training .

from sklearn.model_selection import train_test_split
X_train, X_test, Y_train, Y_test = train_test_split(X, Y, test_size = 0.2, random_state = 0)

📚 Types of ML and their applications

📚 Main ML Algorithms

For different Ml models check this--- click here