Machine Learning, Deep Learning with Python

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Samatrix - Machine Learning

Advanced Machine Learning Course

Learn advanced machine learning course from experts from IIT, IIM, Intel, HP alumni

Certificate with Industry Recognition

Complete the innovative course in Machine Learning and get rewarded with a certificate having industry recognition

Best Machine Learning Course in Industry

Learn the science of machine learning through the No 1 Artificial Intelligence training providers in the industry

Curriculum with Case Studies and Projects

Study the Mathematics and Statistics behind each machine learning model through case studies and projects

Machine Learning Job Market

AI Market
AI Economy Impact

About the Machine Learning Course at Samatrix

The aim of the Machine Learning is to help machine learn automatically with the help of previous examples and past data. Machine Learning is a branch of Artificial Intelligence that focuses on designing the computer applications that observes the data, search patterns, learn from examples and take decisions based on learnings from previous examples. offers an advanced course in Machine Learning. The objective of the course is to help the learner understand the concepts behind each model, clarify the similarities and differences between the models and analyze the results from each model.
The course has been designed to help learners from different industries, educational levels, and experience understand the key concepts of Machine Learning. We cover supervised learning and unsupervised learning in details. The student will get the opportunity to understand regression, classification, tree methods, bagging, random forests, and support vector machine using python, pandas, Numpy, scikit-learn and matplotlib. The student can enroll for Machine Learning training program to avail the benefits of the increased scope of AI in industry.

Key Program Features

Machine Learning Training Program Details

Learn Artificial Intelligence
Technical Course Detail

Course Curriculum

This is an advanced learning program. It requires detailed knowledge of Linear Algebra, Statistics and Python with libraries. For more details please refer Foundation of Artificial Intelligence with Python course

  • What is Machine Learning
  • Machine Learning vs Computer Program
  • Define Machine Learning
  • Application of Machine Learning
  • Relation between variables
  • Supervised Learning
  • Unsupervised Learning
  • Semi-Supervised Learning
  • Reinforcement Learning
  • Prediction
    • Dependent Variable vs Independent Variables
    • Reducible Error and Irreducible Error
    • Expected Value and Variance
  • Inference
    • Which Predictors are associated with Response?
    • Relationship between response and predictors
  • Learning Methods
    • Parametric Methods
    • Non Parametric Methods
  • Model Flexibility vs Interpretability
  • Model Accuracy and Selection
    • Quality of Fit
    • Bias – Variance Trade Off
    • Bayes Classifier
    • K-Nearest Neighbors
  • Multiple Linear Regression
  • Estimating Regression Coefficients
  • Analysis
    • Relationship between Response and Predictor
    • Important Variables
    • Model Fit
    • Predictions
  • Qualitative Regression Models
  • Synergy / Interaction Effect
  • Polynomial Regression
  • Problems with Regression Models
    • Non-linearity of the data
    • Correlation of error terms
    • Non constant variance of error terms
    • Outliers
    • Leverage Points
    • Collinearity
  • Cross Validation
  • Bootstrap
  • Choosing Optimal Model
    • F Test
    • Likelihood Ratio Test (LRT)
    • Akaike Information Criterion (AIC)
    • Bayes Information Criterion (BIC)
    • Adjusted R2
  • Subset Selection
    • Best Subset Selection
    • Forward Stepwise Selection
    • Backward Stepwise Selection
  • Ridge Regression
    • Ridge Regression vs Least Square
  • Lasso Regression
    • Variable Selection Property of Lasso
  • Singular Value Decomposition (SVD)
  • Principal Components
  • Principal Component Analysis (PCA)
  • Geometric Interpretation
  • Polynomial Regression
  • Step Functions
  • Regression Splines
  • Smoothing Splines
  • Local Regression
  • Generalized Additive Models
  • Construct the Tree
  • Regression Tree
  • Classification Tree
  • Impurity Functions
    • Entropy
    • Gini Index
    • Misclassification Rate
  • Tree Pruning
  • Advantages and Disadvantages of Trees
  • Bagging
  • Random Forests
  • Boosting
  • The Challenge of Unsupervised Learning
  • Principal Component Analysis
  • Clustering Methods
    • K-Mean Clustering
    • Hierarchical Clustering
    • Practical Issues in Clustering
  • Introduction to Neural Network
  • Perceptrons
    • NAND Gate
  • Sigmoid Neuron
  • Gradient Descent
  • Multilayer Neural Network
    • Architecture of Multilayer Network
  • Backward Propagation Algorithm
  • Cross Entropy Cost Function
  • Overfitting and Regularization
  • Weight Initialization
  • Meta-Heuristic Optimization
  • Simulated Annealing
  • Particle Swarm Optimization
  • Genetic Algorithms
  • Ant Colony Optimization
  • Differential Evolution
  • Genetic Programming
  • Introduction to TensorFlow
  • TensorFlow Basics
    • Computation Graphs
    • Graphs, Sessions and Fetches
    • Flowing Tensors
    • Variables, Placeholders, and Simple Optimization
  • Introduction to Keras
  • Introduction to Convolutional Neural Networks
  • Introduction to Recurrent Neural Networks (RNN)
  • Auto-Encoders
  • Generative Adversarial Networks

Course Details

Training Location

New Batch Starts - 7 April 2019 and 14 April 2019

Starting 7 April and 14 April 2019 in Gurgaon/Noida. Every weekend for 10 Weeks
April 2019

Training Fee

  • 18% GST Extra
  • Contact Hours - 80+ hours instructor led sessions
  • Additional Practical and Hands-on Hours - 120+ hours
  • Course Duration - 18 Weeks From 14 April 2019
  • Payment Method - Cheque, Netbanking, Demand Draft
In Demand

Admission Process


Selection Process

  1. Fill Application Form: Apply online using the application form
  2. Application Review: Admission committee review the applications submitted
  3. Personal Interview: The Admission committee can invite the applicant for a personal interview.
  4. Admission Offer: The selected candidates would be communicated about their success in admission process

Placement Assistance Program

Samatrix has a dedicated placement assistance team. Under our placement assistance program, we help the learners, who enroll for the program, introduce to our 100+ hiring partners. 

On successful completion of the training requirements, the learner becomes eligible for the training assistance program. Our training assistance team work closely with the learners to understand their career goals and provide mentorship.

We prepare the learners for application process and interviews by conducting resume review workshops, mock HR and technical interviews with industry experts.

Frequently Asked Questions (FAQ)

This program is designed for professionals and students who already have strong knowledge in linear algebra, statistics, and libraries of Python. These concepts are covered in details in our other course Foundation of Artificial Intelligence with Python

This course is designed by assuming that you have a good understanding of the concepts covered in the Foundation of Artificial Intelligence with Python. If you can a good understanding of the concepts or you have already attended a similar course in the past, you can directly join the advanced course.

This is an instructor-led classroom face to face training program. Face to face classroom training helps learners focus on the training program and provides an opportunity to interact with the trainer and other participants.

After successful completion of training program and projects, will issue a certificate of completion of training

Several industry leaders are hiring partners of Our team would help all the learners in job placement. Majority of our trainees have been successfully placed.

The curriculum of Artificial Intelligence Machine Learning training program is very rigorous. This is 135+ hours of instructor led program. The program will start at a designated time on weekends over 4 months. During the course, you will have access to one of the best study material that includes:

  1. Powerpoint presentations
  2. Recording of the sessions
  3. Case study with dataset
  4. Any other relevant study material on the topic

Each learner will have his personal userid through which he can access the study material through the learning management system. Each learner will be provided the access to the LMS for 1 year including course duration

Our Office Locations

Head Office - Gurgaon
Samatrix Consulting Pvt Ltd
311 Vipul Trade Centre
Sector 48, Sohna Road
Gurgaon - 122018
New Delhi
105. Nehru Pl Road,
Block 1, Kalkaji
New Delhi – India
166, Second Floor,
5th Main Road, MC Layout,
Opp BDA Complex,
Karnataka – India
Samatrix Consulting Pvt Ltd
1st Floor,
Near Shakthi Chowk,
Civil Lines
Bijnor – Uttar Pradesh – India


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