Machine Learning with Python or R Training in Bangalore

Learn Machine Learning with Python Course

Best Machine Learning with Python or R Course in Bangalore & Top Machine Learning with Python or R Training Institute


Are you looking for the best Machine Learning with Python or R Training in Bangalore?. Our Machine Learning with Python or R Training Institute in Bangalore will ensure you to understand the Concepts and terminologies of Machine Learning with Python or R with both Theory and Practicals to get real-time understanding and Exposure in Learning Machine Learning with Python or R. Our Machine Learning with Python or R Syllabus and Course Content is crafted by many MNC HR’s and Experts which is as per current Industry requirements and helps you to be one step ahead in the Machine Learning with Python or R field compared to other training institutes.Python training by Bangalore training academy is designed to help you master this extremely popular programming language with ease. Python is a simple interpreter based, high level object- oriented generic programming language and can be used to design and build application and prototype with ease. Best Python Training in Marathahalli & BTM Layout, Bangalore - Learn python course in Bangalore with real-time training from expert trainers and get placement assistance . Bangalore Training Academy offers Python Course Training in Bangalore, Complete the course in 60 days, Get trained on modules like Core python, Advanced python with Live projects. Bangalore Training Academy provides Python development online training and classroom training with live Projects 100% job assurance in BTA technologies In Bangalore.

Our Machine Learning with Python or R Trainers are working professionals with minimum 10+ Years of Expertise in Machine Learning with Python or R Domain and provide training with real-time projects. To know more about Machine Learning with Python or R, Book a Free Demo Class today and get an overall idea of what you are going to learn and scope of doing Machine Learning with Python or R Course as per current Market Trends. We also Provide Lab Facilities, Mock Interviews, Resume Preparation and 100% Placement Assistance to get you placed in Machine Learning with Python or R

Machine Learning with Python Course Syllabus

ü  Artificial Intelligence Course Content In Bangalore

ü  Description

ü  AI is any technique, code or algorithm that enables machines to develop, demonstrate and mimic human cognitive behavior or intelligence and hence the name “Artificial Intelligence”. Some of the most successful applications of AI around us can be seen in Robotics, Computer Vision,

ü  Virtual Reality, Speech Recognition, Automation, Gaming and so on…


ü  Artificial Intelligence is constantly pushing the boundaries of what machines are capable of. The Main purpose of training real time smart machine is to use their speed and capability. Most importantly machine can think and perform task like humans. By this course student will be able to design and develop an advance AI System.

ü  Learning Outcomes

ü  Python Programming for ML

ü  Supervised based algo implementation

ü  Matplotlib for graph plots with linear regression

ü  Live Image Processing

ü  Image Recognition

ü  NLP and Cloud Connectivity

ü  Secured AI with ML and IoT

ü  Introduction

ü  Artificial Intelligence

ü  Introduction to Artificial Intelligence (AI)

ü  History of AI

ü  Importance and other Philosophies about AI

ü  General Approaches and Goals of AI

ü  Components of AI

ü  Working Domains/Companies/Products in Current Market

ü  Programming Languages Used for AI

ü  Python Programming

ü  Python Programming

ü  Basic of python and why python for machine learning

ü  Installation of software on different OS.

ü  Understanding basic syntax with data types

ü  Number, String, List, Tuple, Dictionary

ü  Extracting data from a file

ü  Committing your code to GIT

ü  More About Python Programming

ü  Conditional statement and loops

ü  Function and modules

ü  File handling

ü  Creating own modules / library

ü  Web scraping with urllib2

ü  Grabbing system information from Popen and os library

ü  Scanning Network IP & MAC address with loops

ü  Libraries Used

ü  Introduction to Numpy & Matplotlib

ü  Managing arrary with numpy

ü  Multidimensional array with numpy

ü  Unit matrix handling & creating

ü  Deleting indexes from matrix

ü  Deep dive with Matplotlib

ü  Drawing general purpose graphs

ü  Graphs with mathematics

ü  Machine Learning Techniques

ü  Types of learning

ü  Advice of applying machine learning

ü  Machine learning System Design

ü  Decision Tree Classifier

ü  Training your machine with real time datasets

ü  Deep dive with UCI

ü  Lab session for loading data from different APIs

ü  Detecting data from numpy and converting for training and testing data

ü  testing data

ü  Exercise with ML and others framework

ü  Introduction to iris datasets

ü  Understanding iris datasets

ü  Modifying and loading with scikit-learn

ü  Separating data with numpy

ü  Training classifier

ü  Algo data process view

ü  Decision Tree understanding

ü  Linear Regression

ü  Using House Price Prediction

ü  Simple Linear Regression

ü  Polynomial Linear Regression

ü  Cost Function of Linear Regression

ü  Understanding linear regression using matrix

ü  Logistic Regression

ü  Using Iris dataset to understand logistic regression

ü  Concept of linearly separable data

ü  Cost Function & Mathematical Foundation

ü  Using Iris dataset to understand logistic regression

ü  Concept of linearly separable data

ü  Cost Function & Mathematical Foundation

ü  Neural Networks Analysis

ü  Introduction to Neural Network

ü  Understanding neural networks

ü  Data learning and machine predictions

ü  Neural networks real understanding

ü  Neural network implementation with real datasets

ü  Natural Language Processing

ü  Tokenizing text data

ü  Converting words to their base forms using stemming

ü  Converting words to their base forms using lemmatization

ü  Dividing text data into chunks

ü  Extracting the frequency of terms using a Bag of Words model

ü  Building a category predictor

ü  Constructing a gender identifier

ü  Building a sentiment analyzer

ü  Topic modeling using Latent Dirichlet Allocation

ü  More About ANN

ü  Perception

ü  Back Propagation/Training Algo’s

ü  Convolutional & Recurrent and Artificial Neural Networks

ü  Deep Neural Network

ü  Natural Language Processing (NLP)

ü  Introduction to NLP

ü  Word Representation Model

ü  Sentence Classification

ü  Language Modeling

ü  Project:- Building AI based ChatBot ussing Tensorflow

ü  Feature Engineering

ü  Categorical Features

ü  Text Features

ü  Image Features

ü  Derived Features

ü  Imputation of Missing Data

ü  Feature Pipelines - Transformer & Estimator

ü  Naive Bayes Classification

ü  Bayesian Classification

ü  Gaussian Naive Bayes

ü  Multinomial Naive Bayes

ü  When to Use Naive Bayes

ü  Application : Identify category from text

ü  K-Means Clustering

ü  Introducing k-Means

ü  Understanding cost function for unsupervised algorithms

ü  Elbow rule to decide number of clusters

ü  Application : Image compression

ü  Application : Detection of number of characters in arabic

ü  Decision Trees And Random Forests

ü  Understaning Decision trees

ü  Printing tree

ü  Motivating Random Forests: Decision Trees

ü  Ensembles of Estimators: Random Forests

ü  Random Forest Regression

ü  Application: Random Forest for Classifying Digits

ü  Other Boosting techniques - AdaBoost, Gradient Tree Boosting


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Very competitive and affordable.


Min 7+ Years experience

We have a dedicated students portal

All classrooms are Ventilated with power backups.

We pay Rs 1000 for every student you refer.

Yes its very flexible, you can pay the fees in instalment

We Have Excellent Lab Facility and Provide server access

IT consultants,Solutions Architects, Technical Leads

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Definitely yes we understand the financial situation of each student

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