The Computer Society Chapter, IEEE SJEC Student branch organised a hands-on workshop on ‘Machine Leaing and its Applications by Mr. Mohammed Ameer, founder of Diazonic Labs, Bengaluru - a leading educational company which delivers workshops on various upcoming technologies .
The workshop was conducted for three days from 10 th February, 2020 to 12 th February, 2020. The session was attended by 39 final year students of SJEC. The session was aimed at helping the final year students achieve a deeper and application level understanding in Machine Leaing. The session involved pre-processing, choosing the right algorithm based on each problem statement, model fitting, how over fitting can be avoided, image processing and mini project.
Ms Pramila M, Assistant Professor, Department of Computer Science and Engineering, welcomed the students to the workshop and introduced Mr Mohammed Ameer who was the trainer for the workshop.
Day 1 was a theory and an introductory session on python and various python libraries used for Machine leaing. In the moing session the trainer explained the theoretical aspects of Machine Leaing and how it is different from the usual method of processing the data. An hour was spent on understanding the basics of python and the various data structures that were going to be used for writing the programs for Machine Leaing. The afteoon session involved working with Numpy, Matplotlib and Pandas libraries. The session ended with the trainer giving brief introduction on Machine leaing model and the 9 essential steps to design any model.
Day 2 focussed on how various types of data have to be pre-processed and converted into Data Frame. This involved Web Scraping of statistics of a batsman to derive insights on the batsman’s overall performance. Scikit Lea libraries were used to build the regressors and classifiers. Linear Regression, Decision tree, Support Vector Machine, K-Nearest Neighbours were some of the algorithms whose working and application was taught using the various use cases given by the trainer.
Day 3 involved working with images and video datasets. First half of the day was devoted to leaing the various functions in the OpenCV library which was used to process the image and creating a model from image and video dataset. Latter half involved a mini project where a face recognition application was developed and deploying OCR by Google tesseract on Web by using the Flask framework.
Half an hour was allotted for a Q&A session where students clarified doubts and issues related to their final year projects. The workshop ended with the trainer giving tips on getting better skills and how networking was beneficial for fresher’s in the industry.
