Machine Learning Online Training

Thus by learning machine learning – training of any field can have a bright and better future in the world of artificial intelligence.

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Machine Learning Overview :

Retors Lernen labs introduces interesting concept of computers that is machinelearning. This course provides the data introduction to machine learning, how algorithms used for running programs and other key concepts. There are 4 types of algorithms used for compiling program

  1. Supervised learning which is a mathematical model includes inputs and desired outputs.
  2. Unsupervised learning contains only inputs which structures data using it
  3. Reinforcement learning
  4. Feature learning. By learning this course one can build small robots, understand database mining etc.
What is machine learning?

 It is making computers compute programs by themselves in other words self-automating or process of automation. There are two types of programs traditional and machine learning. The difference between them is in traditional programming program is compiled on the computer to get output and in machine learning program is created by running data and output. It uses algorithms to compile program by itself which are built on sample data. These are used for predictions and decisions to perform the task by the system. Few of the practical applications of these algorithms are email filtering, computer vision. It is also known as predictive analysis as it detects the business problems in advance.

Main features of machine learning are representation, evaluation and optimization. Representation means it helps in how to represent data like sets of rules, graphs, decision trees etc. evaluation includes how to evaluate like cost margins, prediction and recall. Last important component is optimization means search process is included. This course is a vast subject of artificial intelligence which helps in designing algorithms to make predictions based on data.

Why machine learning?

In every field that our everyday life interacts like transportation, media, communication etc. store date in structured and unstructured form so this made an essential step in artificial intelligence to make an application or study which makes machines to learn from data and derive useful insights. This concept is implemented even in self driving cars and in playing chess in our computers where system itself becomes opponent so everything is designed in such a way that depending upon on whatever action we perform like in chess there is a result it gives. One of the latest product of amazon that is echo also applies the same machine learning concept. This has become very powerful processing which makes better decision and gives accurate and inexpensive result.

Few applications of machine learning are data mining, video games, image processing etc. In image processing image tagging and recognition is done, self-driving cars, OCR also implement this module?

Anomaly detection, grouping and association is performed in field like data mining. Reinforcement learning is implemented in few more games. Banks and other businesses in finance field use this learning to identify insights in data and prevent fraud .public safety and utilities use machine learning in analysing sensor data. In health care field

Medical experts analyse data of their patient’s records and suggest treatments. It is useful in many diversified fields like oil and gas to find out minerals and to find new energy sources.

Thus by learning machine learning course of any field can have a bright and better future in the world of artificial intelligence.

Eligibility for taking up this course:

Before taking this course anyone are suggested for prior checking of their eligibility as follows

  • Some high school education in mathematics level.
  • Students who have at least intermediate level studies knowing algorithms.
  • Who wants to build a strong career path in the exciting data science industry
  • Data analyst who want to level up in machine learning.
  • Those who want to become data scientist
  • Basic knowledge is required for any candidate in any training they opt irrespective of their working area
  • It is easy for students to learn machine learning who knows basic algorithms like linear regression, classical algorithms etc.
  • Basic concepts of probability
  • Who have working experience in IT field and who have knowledge on debugging and coding can learn machine learning to move into higher position easily.
Learning outcomes:

Machine learning algorithms are small part of machine learning apart from this we have many outcomes to learn like

  • Applications of machine learning
  • Designing algorithms
  • Make robust machine learning models
  • You can learn algorithms in python and R
  • One can know which machine learning model to be compiled for the type of problem arises.
  • One can make master in machine learning on python and R
  • You can use for personal purpose by learning machine learning.
  • Learn making accurate predictions and powerful analysis.
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Assignment based real time project oriented training

Trainers handpicked from the Corporate World who have got exposure to work with Global MNCs.

Highly interactive and work on very limited batch size to maintain a proper faculty student ratio

After training support in terms of resume preparation and placement