Machine Learning

ML Online Training

Learn Machine Learning and Certification course from Certified Experts.

40 – 80 Hours Duration

100 Assignments

Instructor Led online Training

50 LMS Access

24X7 Support

100% Skill Level

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4.9 out of 1000+ Ratings
Learn Machine Learning from highly experienced, certified working Consultants. This is a project-based training & will be covered with the help of real-time scenario-based projects, tasks & assignment.After the completion of this you will be get certificate for the same.

Overview

  • Imagine a dataset as a table, where the rows are each observation (aka measurement, data point, etc), and the columns for each observation represent the features of that observation and their values.
  • At the outset of a machine learning project, a dataset is usually split into two or three subsets.
  • Once these data subsets are created from the primary dataset, a predictive model or classifier is trained using the training data, and then the model’s predictive accuracy is determined using the test data.
  • As mentioned, machine learning leverages algorithms to automatically model and find patterns in data, usually with the goal of predicting some target output or response.

What you will gain?

  • 1 to 1 Live Online Training
  • Dedicated 24 x 7 Support
  • Flexible Class Timing
  • Training Completion Certification
  • Direct Access to the Trainer
  • Lifetime Access of an LMS
  • Real-time Projects
  • Dedicated Placement Support


Pricing

Beginner Plan

Level A1

Machine Learning

Program Fees:$ 500

$ 400/-

(GST Extra)

Top Hiring Plan

Level A1

ML + AI

Program Fees:$ 600

$ 500/-

(GST Extra)

Advance Plan

Level A1

ML + AI + Tableau

Program Fees:$ 900

$ 800/-

(GST Extra)

For Discounts Call @ +91-72778 77778

Syllabus

  •  Introduction to Machine Learning
  •  Supervised Learning and Linear Regression
  •  Classification and Logistic Regression
  •  Decision Tree and Random Forest
  •  Naïve Bayes and Support Vector Machine (self-paced)
  •  Unsupervised Learning
  •  Natural Language Processing and Text Mining (self-paced)
  •  Introduction to Deep Learning
  •  Time Series Analysis (self-paced)
  •  Time Series Modeling
  •  Ensemble Learning
  •  Recommender Systems
  •  Text Mining
  •  Project Highlights

Benefits of Online Training

  •  100% Satisfaction Ratio
  •  Dedicated Help In Global Examination
  •  Updated Syllabus & On-Demand Doubt Session
  •  Special Group & Corporate Discounts

FAQ’s

Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed. Machine learning focuses on the development of computer programs that can access data and use it learn for themselves.
Machine Learning is a system that can learn from example through self-improvement and without being explicitly coded by programmer. The breakthrough comes with the idea that a machine can singularly learn from the data (i.e., example) to produce accurate results.
Artificial Intelligence is the broader concept of machines being able to carry out tasks in a way that we would consider “smart”. … Machine Learning is a current application of AI based around the idea that we should really just be able to give machines access to data and let them learn for themselves.
Simply put, machine learning allows the user to feed a computer algorithm an immense amount of data and have the computer analyze and make data-driven recommendations and decisions based on only the input data.
However, machine learning remains a relatively ‘hard’ problem. There is no doubt the science of advancing machine learning algorithms through research is difficult. … Machine learning remains a hard problem when implementing existing algorithms and models to work well for your new application.
Artificial Intelligence (AI) and associated technologies will be present across many industries, within a considerable number of software packages, and part of our daily lives by 2020.
The process of training an ML model involves providing an ML algorithm (that is, the learning algorithm) with training data to learn from. The term ML model refers to the model artifact that is created by the training process. … You can use the ML model to get predictions on new data for which you do not know the target.
The training data is used to make sure the machine recognizes patterns in the data, the cross-validation data is used to ensure better accuracy and efficiency of the algorithm used to train the machine, and the test data is used to see how well the machine can predict new answers based on its training.
Model Naming — Give Your Model a Name: Let’s start with giving your model a name, describe your model and attach tags to your model.
Data Type Selection — Choose data type(Images/Text/CSV): It’s time to tell us about the type of data you want to train your model.

Recently Trained Students

Jessica Biel

– Infosys

My instructor had sound Knowledge and used to puts a lot of effort that made the course as simple and easy as possible. I was aiming for with the help of the SAP FICO training imparted to me by this organization.

Richard Harris

– ITC

I got my training from Gaurav sir in the financial accounting module of SAP & I would like to say that say he is one of the best trainers. He has not even trained me but also motivated me to explore more and the way he executed the project, in the end, was mind-blowing.

Job Opportunities

Machine Learning is one of the hottest and most disruptive technologies out there. Machine learning jobs are in extremely high demand. More and more companies are adopting these technologies and this demand is only going to go higher.

The average salary in machine learning makes it a lucrative career option for everyone out there.

Since there is still a long way for this industry to reach its peak, the salary that you make as an ML professional will continue growing with every year. All you need to do is keep upskilling and updating yourself.

Know more

Job Designation

  • Data Scientist
  • Machine Learning Engineer
  • Machine Learning Scientist
  • Applications Architect
  • Enterprise Architect
  • Data Architect

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