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Machine Learning & Deep Learning Internship/Training Program - September 2022

(Batches Start from 26th September 2022)

About The Program:

With the belief to build a healthy ecosystem as per the Industry Standards REGex Software brings an Industrial Training/Internship Program on “Machine Learning and Deep Learning”. We organize Machine Learning and Deep Learning Program for improving the knowledge and skills of the Students/Professionals, so that they can become specialized in the field of Machine Learning and get their Dream Job in Software Development Field in Big MNCs.

REGex Software Services’s “Machine Learning and Deep Learning” program is a valuable resource for beginners and experts. This program will introduce you to Python, Machine Learning, Deep Learning etc. from Basics to Advance. If you want to become Machine Learning Expert, REGex introduce this program for you.

Timing

09:00 PM – 11:00 PM (IST)
(Mon – Fri)

Platform

Google Meet

Duration

6 – 8 Weeks

Participants

50 per Batch

Pause Your Program

You can pause your program if you have any Medical Emergency or if you have Exams and join again our new program within next 3 Months

What People Tell About Us

Best affordable Python + Django program with live classes and doubt solving. You can also access to recordings of the classes. Teachers and mentor are very good. All syllabus covered in given time. With multiple live examples. Best part of training is friendly environment. Don't hesitate to enroll if you've never heard the name of this company before. You will not be disappointed.

Shubham Katkar Ex-Student, Django Batch

Competitive Programming is the best course they have - i am part of both python and C++ course. Cracked several interviews with their course, poll test & assignment are always new and beneficial. Best CP course you will find here, i hope this will be beneficial for you

Yaman Singh Ex-Student, CP Batch

Tushar sir is best in delivery. His approach is mind blowing. I have not found any gap although I am from U.S Lots of Big Data tools I have learnt like Hadoop, Hive, Spark, Sqoop & most amazingly Talend ETL Tools which was the most lovely part of training. every component is told in very simple terms with great practical approach

Josh Well Ex-Student, BigData Batch

I recently joined Python Django(Web Development - Full Stack)Course About Course: - I must say instructor makes every concept simple to understand - No Copy Paste,Every line of code is explained - Even given Assignments to work on - Even given Projects to work on If you looking to learn Python Django I highly recommend to go for this course

Salman Khan Ex-Student, Django Batch

I am from UK & loved the teaching. Competitive Programming was the best experience I had in coding. I can truly say the money I spend is worth it. Go for it guys!!

Jack Ryan Ex-Student, CP Batch

What you will Learn

Python

Duration: 25 - 30 Hours

Machine Learning

Duration: 35 - 40 Hours

Deep Learning

Duration: 35 - 40 Hours

Study Material

  • E-Notes
  • Assignments & Poll test
  • 100+ hours on demand Live Video Lectures
  • Access of Recordings & Study Material
  • Mentorship Support
  • Work on multiple Minor Projects & Use Cases
  • Work on Live Projects

Output

  • Able to think out of the box
  • Become expert in multiple technology domains like: Python, Machine Learning, Deep Learning
  • Understand working of ML models deployment with AWS
  • Build projects on multiple technology domains
  • Work on Use CASES & Projects
  • Learn to deploy your models on AWS Sagemaker or Google cloud Platform

Live Sessions

Live Sessions by Expertise Trainers and Access of Recorded Session is also available

Live Projects

Get a chance to work on Industry Oriented Projects to implement your learning

24*7 Support

24*7 Mentorship Support available for all Students to clear all of your doubts

Opportunities

REGex provides Internship / Job opportunities to the best Students in different Companies.

Our Students Placed In

Previous
Next

Course Content

Machine Learning

  • Machine learning applications
  • ML vs DL
  • Basics of Python [Syntax]
  • Working with Pandas, Numpy & Matplotlib
    ■ Working with Missing Data
    ■ Data Grouping
    ■ Data Subsetting
    ■ Merging & Joining Data Frames
  • Importing Libraries & Datasets
  • Munging & handling missing data
  • Splitting the dataset into Training set & Test set
  • What is actual machine learning
  • Various Aspects of Data – type, Variables & Category
  • Machine Learning & its Various types
  • About Supervised & Unsupervised Learning
  • Understanding Simple Linear Regression
  • Understanding the P -Value
  • Support Vector Regression
  • K nearest neighbours
  • Logistic regression
  • Naive Bayes
  • Decision trees
  • Random forests
  • Bagging Boosting
  • Maximum likelihood classifier
  • Support vector machines

  • Principal Component analysis (PCA – Theory)

  • PCA with Case-Study

  • Linear Discriminant Analysis(LDA) for Dimension Reduction

  • Feature Selection to Select the Most Relevant Predictors

  • Confusion matrix

  • Accuracy Paradox

  • CAP Curve

  • K-Mean Clustering Intuition

  • K-Mean selecting Numbers of Cluster

  • About Reinforcement Learning

Deep Learning

  • NLP Intuition

  • Types of NLP

  • Classification vs Deep Learning Models

  • The Neuron

  • Activation function

  • How Neural network work & learn by itself

  • Gradient Descent

  • Stochastic Gradient Descent

  • Ethics of Deep Learning

  • What are convolutional neural networks [CNN] ?

  • CNN Architecture

  • CNN Code preparation

  • Recurrent Neural Networks

  • Several layers

    ■ ReLLu Operation

    ■ Pooling

    ■ Flattering

    ■ Full Connection

  • Statistics

  • Sample Selection

  • Probability Theory

  • Hypothesis

  • Model Relationship

  • Model Fit

  • Descriptive Statistics

  • Types of Data

  • Qualitative Data

  • Histograms

  • Different Plots

  • Centrality and Spread

  • Outliers

  • Median, Mean, Mode

Computer Vision

  • What is computer vision & its application

  • Face Detection

    ■ Adding more features & Categorization

    ■ Object Detection & Image creation

    ■ Working with Images & vectors

  • Facial Expression Recognition in Code (Binary / Sigmoid /Logistic Regression)

  • Object detection

  • Neural style transfer

  • YOLO

  • RCNNs

  • Resnet 50

  • Tensorboard

  • What are Vectors

  • Working with word Analogy

  • Text Classification

  • Pre Trained word vectors from word2vec

  • Language Models

  • Introduction to Tensorflow / Keras

  • Most used right now

  • Resources gathering

  • Keras dealing with Missing Data

  • Dealing with Categorical data

Model Deployment & Projects

  • Create your own ML models
  • Deploy ML models
  • AWS Recognition
    • Titanic Classification
    • Carbon Emissions
    • Car price analysis
    • Drug Prediction
    • Hand written Digit Recognition
    • CIFAR 10
    • CIFAR 100
    • Cats vs dogs
    • Intel scene Classification
    • Transfer Learning
    • Object Detection

Extra Sessions

Additinal Session on GIT, Linux, Docker, AWS Basics, Jenkins and many more for all students.

Fee Structure

Indian Fee

Price: ₹39999/- (Flat 75% off) => ₹9999/- 

International Fee

Price: $1000 (Flat 75% off) => $250 

Fee can be paid in 2 installments of 6k + 5k

Cashback Policy

  • You will get your Unique Referral Code after successful paid registration.
  • You will get ₹1000 Cashback directly in your account for each paid registration from your Unique Referral Code on 30th September, 2022(After Closing Registrations of this program) .
  • For Example:- If we received 10 paid registration from your Unique Referral Code then you will receive ₹1000*10 = ₹10000 on 30th September, 2022.
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(Batches Start from 26th September 2022)

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*Seats can be filled or Price can be increased at any time. Refund policy is not available*