Machine Learining Training Syllabus

The only Machine Learning training program
where you get in-depth knowledge of all the modules of Machine Learning
  • Introduction to Big Data and Machine Learning
  • Understanding Python and R
  • Types of Learning
  • Advice for Applying Machine Learning
  • Machine Learning System Design
  • Basics of Statistics
  • Data cleaning
  • Data Exploration
  • Statistical Inference
  • PGM (Probabilistic graphical model)
  • Regression
  • Simple linear regression
  • Multiple linear regression
  • Assessing performance
  • Ridge Regression
  • Features selection and lasso
  • Nearest neighbours and kernel regression
  • Classification
  • Decision Trees and CART
  • Support Vector Machines(SVM)
  • Naive Bayes
  • Project work – Cancer Detection, Fraud Analysis, Spam Filter creation
  • Clustering
  • Overview
  • Types of Clustering
  • Types of Clustering Algorithms
  • K Means Clustering
  • Hierarchical Clustering
  • Difference between K Means and Hierarchical clustering
  • Applications of Clustering
  • Project Work: Social Media Analysis with Clustering
  • Basics of NLP
  • Text Extraction
  • Sentimental Analysis
  • Similarity matric learning
  • Infromation Retrival
  • Recommender System Overview
  • Phases of Recommendation Process
  • Recommendation filtering Techniques
  • Evaluation metrics for recommendation Algorithms
  • Spark Core
  • Spark Architecture
  • Working with RDDs
  • Machine learning with Spark – Mllib
  • The Perceptron learning procedure
  • The back propagation learning procedure
  • Learning feature vectors for words
  • Object recognition with neural nets
  • Optimization: How to make the learning go faster
  • Recurrent neural networks
  • More recurrent neural networks
  • Ways to make neural networks generalize better
  • Combining multiple neural networks to improve generalization
  • Hopfield nets and Boltzmann machines
  • Restricted Boltzmann machines (RBMs)
  • Stacking RBMs to make Deep Belief Nets
  • Deep Learning
  • Convolutional Neural Network(CNN)
  • Object Detetcion
  • Object Classification
  • Localization
  • Edge Detection
  • Stride, Padding
  • YOLO algorithm
  • Introduction
  • AI roots and applications
  • Propositional calculus
  • Predicate calculus
  • Prolog and Lisp
  • Syntax
  • Data Types
  • Control Mechanisms
  • Case-based Reasoning
  • Model-based Reasoning
  • Hybrid Models
  • Graph Theory & Finite State Machine
  • State Space Search Algorithms
  • Reasoning Strategies
  • Concepts
  • Issues
  • Ontologies & Agent Based Systems
  • Heuristic Search Issues
  • Heuristic Search Applications
  • Hill Climbing algorithm
  • Dynamic programming
  • Best-first search
  • Related Issues
  • Recursion-based Searching
  • Production and Blackboard Systems Architecture

Still Hunting for a Job? (or) Want to Make a Career Switch into Machine Learning Tools ?

Recruiters are looking for you!

All you need is Learn A-Z of Machine Learning Tools with Indrasacademy Training in Bangalore

Become Machine Learning Certified Professional And Get Placed with our Free Placement Program

Enroll Your Name Now

Machine Learning Cources In Bangalore



Know which Machine Learning tools are most relevant

Indras Academy provides best Machine Learning training in Bangalore Marathahalli. Our machine learning is handled by working professionals with real-time experience. Machine Learning (ML) is a different approach where computer learns the rules of solving complex problems without explicitly programmed. Machine Learning algorithms are at the core and important piece of data science. This course - Machine Learning Foundation, is designed to provide a holistic understanding of various ML algorithms with high-level theory and hands-on application of ML algorithms to classic data sets.


Enroll Your Name Now

Register Now

For Demo Class!!


Your Full Name
Your EMail
Mobile

We Have Trained
More Than 2500+ Students

  • 2000+

    Professionals Trained

  • 200+

    Batches

  • 9.8/10

    Rating given by trainees

Frequently Asked Questions

The only Machine Learning training program
where you get in-depth knowledge of all the modules of Machine Learning

Machine learning is taking over the world- and with that, there is a growing need among companies for professionals to know the ins and outs of machine learning The machine learning market size is expected to grow from USD 1.03 Billion in 2016 to USD 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period

A form of artificial intelligence, machine learning is revolutionizing the world of computing as well as all people’s digital interactions. By making it possible to quickly, cheaply and automatically process and analyze huge volumes of complex data, machine learning is critical to countless new and future applications. Machine learning powers such innovative automated technologies as recommendation engines, facial recognition, fraud protection and even self-driving cars.

By the end of this Machine Learning course, you will be able to accomplish the following: Master the concepts of supervised, unsupervised and reinforcement learning concepts and modeling. Gain practical mastery over principles, algorithms, and applications of machine learning through a hands-on approach which includes working on 28 projects and one capstone project. Acquire thorough knowledge of the mathematical and heuristic aspects of machine learning.

There is an increasing demand for skilled machine learning engineers across all industries, making this Machine Learning certification course well-suited for participants at the intermediate level of experience. We recommend this Machine Learning training course for the following professionals in particular: Developers aspiring to be a data scientist or machine learning engineer Analytics managers who are leading a team of analysts Business analysts who want to understand data science techniques Information architects who want to gain expertise in machine learning algorithms

There is an increasing demand for skilled machine learning engineers across all industries, making this Machine Learning certification course well-suited for participants at the intermediate level of experience. We recommend this Machine Learning training course for the following professionals in particular: Developers aspiring to be a data scientist or machine learning engineer Analytics managers who are leading a team of analysts Business analysts who want to understand data science techniques Information architects who want to gain expertise in machine learning algorithms

Simplilearn’s Machine Learning course is a hands-on, code-driven training that will help you apply your machine learning knowledge. You will work on 4 projects that encompass 25+ ancillary exercises and 17 machine learning algorithms.

Participants in this Machine Learning online course should have: Familiarity with the fundamentals of Python programming Fair understanding of the basics of statistics and mathematics.

Participants in this Machine Learning online course should have: Familiarity with the fundamentals of Python programming Fair understanding of the basics of statistics and mathematics.

Find US