About Machine Learning

Machine learning is a broad and fascinating field. It has been called one of the sexiest fields to work in. Machine learning has become an integral part of many commercial application and research projects.It has applications in an incredibly wide variety of areas, from medicine to advertising, from military to pedestrian.Its importance is probably going to grow, as a lot of and a lot of areas intercommunicate it as some way of addressing the huge amounts of data available.At a basic level, machine learning is concerning predicting the longer term supported the past.

In Our training Program, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you’ll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems.

Why Machine Learning

Machine learning has several very practical applications that drive the kind of real business results, such as time and money saving, that have the potential to dramatically impact the future of your organization. Machine learning is allowing people to get things done more quickly and efficiently. Through Virtual Assistant solutions, machine learning automates tasks that would otherwise need to be performed by a live agent – such as changing a password or checking an account balance.

  • Machine learning automates the process of examining several databases to collect valuable information
  • Machine learning helps to improve based on the past experience
  • Machine learning can easily consume unlimited amounts of data with timely analysis and assessment
  • Fast Processing and Real-Time Predictions
  • Facilitates Accurate Medical Predictions and Diagnoses
  • Simplifies Time-Intensive Documentation in Data Entry
  • Increases the Efficiency of Predictive Maintenance in the Manufacturing Industry
  • Better Customer Segmentation and Accurate Lifetime Value Prediction

Course Description

Machine learning usesinterdisciplinary techniquessuch as statistics, linear algebra, optimization, and computer science to create automated systems thatcan sift through large volumes of data at high speed to make predictions or decisions without human intervention.Machine learning as a field is now incredibly pervasive, with applications spanning frombusiness intelligenceto homeland security, from analyzing biochemical interactions to structural monitoring of aging bridges,and from emissions to astrophysics, etc. This class will familiarize studentswith a broad cross-section of models and algorithms for machine learning, and prepare studentsfor research or industry application of machine learning techniques.

Overview

Based on fundamental knowledge of computer science principles and skills, probability and statistics theory, and the theory and application of linear algebra. This course provides a broad introduction to machine learning and statistical pattern recognition. Topics include:

(1) supervised learning (generative/discriminative learning, parametric/non-parametric learning, neural networks, and support vector machines)

(2) unsupervised learning (clustering, dimensionality reduction, kernel methods)

(3) learning theory (bias/variance tradeoffs; VC theory; large margins)

(4) reinforcement learning and adaptive control. The course will also discuss recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing.

Learning Outcomes

By the end of the course, students should be able to:

  • Develop an appreciation for what is involved in learning models from data.
  • Understand a wide variety of learning algorithms.
  • Understand how to evaluate models generated from data.
  • Apply the algorithms to a real-worldproblem, optimize the models learned and report on the expected accuracy that can be achieved by applying the models.

COURSE REQUIREMENTS

1. Regular class attendance is the main requirement of this course.
2. Active class participation, this means you must spend some quality time preparing for your next class.
3. Programming assignments, homework, and reports of hands-on labs must be turned in on time when they are due. Unfinished programs and non-working programs turned in on time will be graded; however, assignments not turned in on the due date will NOT be accepted. This means that you should start early to work on your programming assignments. Programs must be well-documented to be understood by a novice programmer.
4. Short quizzes may be given without prior notice and there will be no making up of missed quizzes.
5. Two examinations and a final examination will be given. There will be NO make up for missed exams.
6. You will be issued with one computer account for this class. You have a responsibility and an obligation to prevent abuse and misuse of the university computer resources. Please read the UTC Computer Use Code of Conduct.
7. Individual extra credit assignments for the purpose of propping up a bad grade will NOTbe given.

Go Beyond Your Wildest Dreams

Why choose Kryptora?

You will get a refund on your investment with our industrial training or online training. Your investment in the course will be rewarded many times over. Kryptora Infotech has a very good track record of delivering new organization, money-saving, and extra profit to our customer.

Training has remained both functional and interesting with lots of joy. Courses are customized and kept relevant using case studies and examples from your industry. Management is consulted throughout the training process to clearly determine what success is.

The Sky's The Limit

OVER THE INDIA

We have the business all over India, we have mainly 4 branches at the time. Which are available in different cities like Delhi, Noida, Meerut, Patna, and Kolkata.

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