@ about workshop
At first, tutors make us learn the basics of python[About Python, List, Tuple, and Dictionary] and they gave some hands-on practice in python. Then we moved to a few libraries like Numpy, Pandas, and Scikit-learn which will be used for data manipulation and data cleaning(Data Science). For hands_on practice they provide some data sets in text, excel and CSV format. We applied few cleaning techniques using the above-mentioned libraries and we performed data cleaning(i.e: to read the data using read_ function, changed the columns to required data type formats, filled the blank spaces with mean or meridian values using fillna function, etc) then we represented the cleaned data pictorially by graphs [bar graph, scatter plots, histogram e.t.c] using matplotlib or seaborn library . Then we moved to the basics of machine learning concepts. In machine learning, we learned about Linear regression(Function) and Logistics regression(Classification) from supervised machine learning. We build a model i.e performed prediction and analysis on cleaned data using both linear and logistics regression.
Everyone is unique, very friendly and well knowledged in concepts. Though our doubts are so silly, they cleared our doubts without any hesitation, which makes us feel very comfortable. They show interest in each and everyone and they want every one of us to be clear in our workshop concepts. Thanks to you all for all your help and guidance.