B. Jansepyara

An astute and result-oriented professional having 1.5-year experience in BFSI sector, with a keen interest toward the Data Science role, proficient in Data Science with a focus on Model Building, Data Pre-processing, Data Visualizing, and Data Mining algorithms as well as scripting language including python. Capable of solving complex business problems from the data and extracting the meaningful insights for the growth of the organizations.

GitHub: janse99 (B.JANSEPYARA) (github.com)

Kaggle: janse official | Novice | Kaggle

LinkedIn: B. Jansepyara | LinkedIn

GL Academic e-Portfolio: Eportfolio - Great Learning (mygreatlearning.com)

• Prediction of Duration of Stay in Hospital For each Patient: -
• Objective: -The task is to accurately predict the Length of Stay for each patient on case-by-case basis so that the Hospitals can use this information for optimal resource allocation and better functioning
• Summary: - As a part of my Capstone project, we developed a machine learning model to predict the length of stay of each patient for a non-profit hospital
• Performed Data Cleaning, Data Pre-processing, build base models and finally we improve the performance of our base model and compare with all others models and choose the best out of it
• Technologies Used: -Python, Scikit-learn, Stats models, Yellow bricks, NumPy, Pandas, Seaborn, Matplotlib
• Skills Developed: - Machine Learning, Feature Engineering, Clustering, Data Visualisation
• Food Demand Forecasting: -
• Objective: -The task is to forecast the demand for upcoming weeks so that these centres will plan the stock of raw materials accordingly
• Summary: - I developed a machine learning models to forecast the food demand for each centre
• Performed Data Cleaning, Data
• Pre-processing, build base models and finally improve the model performance and compare with all others models and choose the final models and predict the result
• Technologies Used: -Python, Scikit-learn, Stats models, Yellow bricks, NumPy, Pandas, Seaborn, Matplotlib
• Skills Developed: - Machine Learning, Feature Engineering, Data Visualisation
• Black Friday Sales Prediction: -
• Objective: - The task is to predict the customer purchase amount against various products of different categories which will help them to create personalized offer for customers against different products
• Summary: - I developed a machine learning model to predict the purchase amount against each customer id and product id
• I build the base model and see the accuracy and try different machine learning model and improve the
• Accuracy
• Finally compare with all the model and select the final model with highest accuracy and predict the final result
• Technologies Used: -Python, Scikit-learn, Stats models, Yellow bricks, NumPy, Pandas, Seaborn, Matplotlib
• Skills Developed: - Machine Learning, Feature Engineering, Data Visualisation, Statistical Analysis
• HACKATHONS: - Data Verse Hack Insurance Claim Prediction by Analytics Vidhya Janta Hack Health Care Analytics by Analytics Vidhya Taxi Trip Fare Predictions Challenge by Machine Hack Digit Recognizer (Image Classification) by Kaggle Titanic Machine Learning Disaster by Kaggle Big Mart Sales Prediction by Analytics Vidhya House Price Advance Regression Technique by Kaggle