I will update this repository to learn Machine learning with python with statistics content and materials

Day - 1: 6-4-2019 We Learnt about Different types of Analytics Different types of Machine Learning Why Python? Features of Python

Day - 2: 7-4-2019 We Started practising the python Ways to implement python Why Jupyter notebook? What is keyword, variable? Conditions on creating a identifier Different datastructure List, Tuple, Set, Dictionary, String Typecast

Day - 3: 13-4-019 Control Sataement Condition Statement What is Indendation? Functions Paraments, Defaut Parameters, Arbitory Parameters

Day - 4: 14-4-2019 Recursive Function Lambda Function Map, Filter, Reduce List Comprehension Set Comprehension Try, Except, Finally

Day - 5: 27-4-2019 Class and Object OS Library Module in python import and from import Numpy: Why Numpy? Numpy Basics

Day - 6: 28-4-2019 Pandas Data Loading Data Manipulation Data Filtering Data Grouping

Day - 7: 04-05-2019 What is Data Preprocessing? Why Data Preprocessing? Diferent Technique of Data Preprocessing Data Preprocessing with pandas example

Day - 8: 05-05-2019 Part - 1: What is Statistics? What are the Data types? Different measures - Central Tendency and Dispersion Percentiles, Quartiles and Box - Plots

Day - 9: 11-05-2019 Part - 2: Examples understanding indetail Concepts of Descriptive Statistics of Part - 1, Correlation, Covariance and Visualization

Day - 10: 12-05-2019 Part - 3: Explaining Sampling bias, Various Sampling techniques, Characteristics of Normal Distribution and empirical rule, Central Limit Theorem, Standard Error, Z - Score, Confiedence Intervals