Hi 👋, I'm RAMANSH!
I am 21 years old and pursuing a degree in B.tech Computer Science at ABES Engineering College.
I visualize the data using different kinds of graphs and create dashboards for a better story-telling and understanding the data.
Building the ML models using various kinds of algos according to the problem statement. It also includes data preparation and accuracy measure.
Deploying the ready-made model on different platforms to get the most value out of machine learning models.
Let's Grow More(Summer Of Code).Joined as an open source contributor in the domain of Machine Learning and Data Science.Looking forward to contribute and be a part of open source
It was a research-based internship in which our team had to create an ML model or a Deep Learning model based on some social causes. My team created an ML model based on 'Mental Health Issues in Tech World'.
I was a Data Science and Business Analytics Intern where we were provided day to day tasks to implement various ML algorithms on given data sets and visualization.
I am a budding data scientist and an analyst working in the domain of Data Science and Data Analytics for more than a year now. Passionate about coding and ability to perform well in a team. Loves to learn skills that help me to be a better person physically and mentally.
Hi! This is Ramansh Sangal
Currently I am a student of ABES Engineering College pursuing B.Tech from CSE Branch with an aggregate of 80.11%. I am also a MACHINE LEARNING engineer with fluent hands-on experience of SkLearn framework and other supporting python libraries along with model deployment. I also have experience of Tableau which is a business analysis tool.
Feel free to download the resume below for more information about me!!
It was an end to end Machine Learning project which predicted the flight fare based on some input features. It has an accuracy of almost 80%.The model was deployed using Heroku
This a Tableau dashboard project. It analyzes the trend of FDI(foreign direct investment) of various sectors in India.
It was a regression project which basically tells us the estimated price of a real estate, particularly in Bangalore. The dataset was taken from Kaggle. In this project, data cleaning was the major part. It outputs the price of real estate with an accuracy of almost 84%.
This was more of a data collection and cleaning project. It estimated the salary of an employee who works in the field of data science based on various factors such as Company Name, Company Rating, Size of Company and Job Title.
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