Machine Learning is the next big technology and is expected to have wide impact on our lives in coming years. It is a technology to make computers to think like human beings, to make decision making based on facts and data. Machine Learning and Artificial Intelligence are related fields.

We have designed the Machine Learning course content to suit the needs of engineering undergraduates and professional who want to pursue their career in the field of Machine Learning and Artificial intelligence in a number of domains.

Benefits of Summer Training:

• Provide students the in-depth hands on knowledge software development life cycle.
• Students get a chance to apply what that they learn  in their course curriculum.
• A environment of working life for students.
• Helps student in deciding the kind of specialization they want to pursue.
• Learn & Interact with renowned Industry Experts.
• Practical learning based Training Program.
• Receive an unparalleled education on the art of personality development with personal one-on-one attention.
• Get thorough insight into Industry Standard.
• Hands on Demonstrations of Latest Technologies.
• Will also include personality development and Technical skills.
• Will also include Interview preparation skills.
• Placement Assistance to students attending our training.

Course Contents:

Machine Learning

Introduction to Machine Learning  | Datatypes | Operators | Flow Control | Looping Techniques | Python Modules | Python Packages | Tuples | File Handling | Basics of AI & Introduction | Fuzzy Logic | Linear Regression | Decision Trees | Artificial Neural Networks | Support Vector Machine | Image Processing with Opencv | Clustering | Deep Learning Networks | Introduction to TensorFlow | Convolutional Neural Networks | Natural Language Processing | Examples of Machine Learning Applications | Modelling Regression Analysis | Creating a Clustering Model | Loan Prediction Problem | Working on Iris Data Set

Machine Learning with Data Analytics

1. Introduction To Python
Python Datatypes,
Data Structure
Functions
Looping Techniques
Python Modules
Python Packages
Libraries
Installing Pandas,Numpy,Scipy,Scikit,Matplotlib etc.

2. Introduction to Data Mining
Stages of the Data Mining Process
Data Mining Goals
Information and Knowledge
Advantages in Data Mining
Related technologies – Machine Learning, DBMS, OLAP, Statistics
Data Mining Techniques
Role of Data Mining in Various Field like Artificial Intelligence and Internet of Things

3. Machine Learning
Supervised & Unsupervised Learning
Regression Analysis
Linear Regression and Logistic Regression
Classification
Prediction
Bayesian Classification Models
Association rules
Neural Networks
Perceptron
MLP
SVM

4. Hands On Project
Modelling Regression Analysis
Creating a Clustering Model
Loan Prediction Problem
Working on Iris Data Set
Titanic Data
Boston Housing Data Set
Predict Stock Prices
Classifying MNIST digits using Logistic Regression
Intrusion Detection using Decision
CIFAR Data set
ImageNet Data Set
Credit Risk Analytics using SVM in Python