PYTHON

Python - Introduction

  • About - Python
  • Environment Setup
  • Syntax
  • Operation With String
  • Conditional Operators
  • Condition
  • Logical Operators
  • Bitwise Operators
  • Mathematical Operators
  • List/Array/Tuples
  • Shorting/Slicing/Indexing
  • Looping
  • Function
  • Classes
  • Regular Expression
  • Inheritance
  • Lambda/Map/Filter/Reduce
  • Error-Handling
  • Recursive Function
  • File Handling(Open/Os/Shutil/Glob)
  • Date/Date-time/Scheduler

Pandas

  • About Pandas
  • Environment Setup
  • Introduction to Data Structures
  • Series
  • DataFrame
  • Panel
  • Input/Output
  • Basic Functionality
  • Iteration
  • Indexing
  • Sorting
  • Missing Data
  • Concatenation
  • TimeDelta
  • Categorical -Data
  • Statistical Function
  • Group-By
  • Merging/Joining

Numpy

  • Intro To Numpy
  • Basic Maths Of Matrix
  • Matrix Claculation
  • Environment Setup
  • Ndarray Object
  • Data Type
  • Indexing-Slicing
  • Advanced Indexing
  • String Function
  • Mathematical Function
  • Matrix Function
  • Linear Algebra
  • Arithmatic Operation
  • Matrix Library
  • I/O With Numpy
  • Iterating Over Array
  • V-Stack
  • H-Stack
  • Dot-Product
  • Determinant In Numpy
  • Inverse of matrix
  • Transeverse of matrix

MatPlot Library

  • Introduction
  • Environment Setup
  • Basic Of Co-ordinate
  • Scatter
  • Plot
  • Bar Graph
  • PieChart And Types
  • 3-D Scatter
  • 3-D Plot
  • 3-D Bar Graph
  • Heat Map
  • Date And Time Handling
  • Application On RealTime Data
  • Application On Share Market Data
  • Wave Plot
  • 3-D WireFrame

Data-Pre-Processing (SK-Learn)

  • Requirement Of Data Preprocessing
  • Getting Data From Source
  • Getting Required Data From Raw Data
  • Handling Missing Data
  • Label Encoding
  • Categorical Encoding
  • Standardisation Of Data
  • Breaking Data For Cross Validation

Machine Learning(SK-Learn And Scratch)

  • Linear Regression
  • Multiple Regression
  • Polynomial Regression
  • SVR
  • Decision Tree(For Regression)
  • Random Forest(For Regression)
  • KNN(For Classification)
  • Logistic Regression(For Classification)
  • Naive Bayes(For Classification)
  • SVM
  • SVM Kernel
  • Decision Tree(For Classification)
  • Random Forest(For Classification)
  • K-Means(For Clustering)
  • Hierarchical Model(For Clustering)

Deep-Learning (Using Tensorflow And Keras)

  • About ANN
  • ANN From Scratch
  • Tensorflow Basic
  • ANN Using Tensorflow
  • ANN Using Keras
  • CNN Basic
  • CNN For Image Classification
  • CNN Using Tensorflow And Keras