National Workshop on Machine Learning: Conducted on 27.01.2020


The inaugural program on machine Learning was started today i.e. 27.01.2020 with the arrival of Guests and experts Mr Rajat Goyal and Sachin Yadav from Brass Solutions Pvt Ltd, Jaipur. Prof. D G Mahto welcomed the guests with Bouquet. Prof. Sunita Rawat and Dr. Bharat Bhushan along with other faculty members were present at the inaugural. The inaugural function was started with the lamp lighting ceremony.Welcome and about importance of workshop and its schedule were explained to the participants. 

The workshop was scheduled in two basic categories 1. Theoretical and 2. Hands on Practicals with tasks of assignments in the form of projects

The starting session was on basics of Machine learning. In this session the topics covered are like What Is Machine Learning?  Categories Of Machine Learning,  Supervised Learning, Unsupervised Learning , Reinforcement Learning , Deep Learning  Deep Reinforcement Learning etc were covered

Similarly in the 2nd session, the participants were made familiar with in detail about:

  • What is the heart of machine learning?
  • What are the different algorithms available for developing machine learning models?
  • What are the programming language choices?
  • What platforms support development and deployment of Machine Learning applications?
  • What IDEs (Integrated Development Environment) are available?

The after lunch sessions were hands on practice and doubt clearing session. The examples of Google was taken. The brief of one example is as follows:

We all use Google Directions during our trip anywhere in the city for a daily commute or even for inter-city travels. Google Directions application suggests the fastest path to our destination at that time instance. When we follow this path, we have observed that Google is almost 100% right in its suggestions and we save our valuable time on the trip.

You can imagine the complexity involved in developing this kind of application considering that there are multiple paths to your destination and the application has to judge the traffic situation in every possible path to give you a travel time estimate for each such path. Besides, consider the fact that Google Directions covers the entire globe. Undoubtedly, lots of AI and Machine Learning techniques are in-use under the hoods of such applications. Considering the continuous demand for the development of such applications, you will now appreciate why there is a sudden demand for IT professionals with AI skills.

During the practice session participants were given advises on Language Choice and instructed to be familiar with the following languages

  • Python
  • R
  • Matlab
  • Octave
  • Julia
  • C++
  • C

At some stage in the project work execution, IDEs were part of discussion. The experts described that the following support ML development in better way:

  • R Studio
  • Pycharm
  • iPython/Jupyter Notebook
  • Julia
  • Spyder
  • Anaconda
  • Rodeo
  • Google –Colab

The experts explained the usage and advantages of Platforms like

  • IBM
  • Microsoft Azure
  • Google Cloud
  • Amazon
  • Mlflow

Finally, it was summarized that Machine Learning can be a Supervised or Unsupervised. If you have lesser amount of data and clearly labelled data for training, opt for Supervised Learning. Unsupervised Learning would generally give better performance and results for large data sets. If you have a huge data set easily available, go for deep learning techniques. You also have learned Reinforcement Learning and Deep Reinforcement Learning. You now know what Neural Networks are, their applications and limitations.

In conclusion, when it comes to the development of machine learning models of your own, you looked at the choices of various development languages, IDEs and Platforms. Next thing that you need to do is start learning and practicing each machine learning technique. The subject is vast, it means that there is width, but if you consider the depth, each topic can be learned in a few hours. Each topic is independent of each other. You need to take into consideration one topic at a time, learn it, practice it and implement the algorithm/s in it using a language choice of yours. This is the best way to start studying Machine Learning. Practicing one topic at a time, very soon you would acquire the width that is eventually required of a Machine Learning expert.

The one day workshop was most fruitful with interesting and stimulating discussions and exchange of knowledge. It was expected that participants must have value additions through this National Workshop which will be useful in their professional life. The workshop was ended with valedictory, certificate distribution and vote of thanks.

The images of the various sessions of the national workshop are attached here with for information and sharing with the participants and interested ones