This Portfolio is a compilation of all the Data Science and Data Analysis projects I have done for academic, self-learning and hobby purposes. This portfolio also contains my Achievements, skills, and certificates. It is updated on the regular basis.
- Email: phadtaredeepak001@gmail.com
- LinkedIn: linkedin.com/in/deepakphadtare
Instacart Market Basket Analysis
The objective of this project is to analyze the 3 million grocery orders from more than 200,000 Instacart users and predict which previously purchased item will be in user's next order. Customer segmentation and affinity analysis are also done to study user purchase patterns.
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Created seven disease classification models with TensorFlow, Random Forest and XGBoost to analyse patients’ medical records, achieving over 90% accuracy. Integrated trained models to create an application with Flask framework.
Developed an innovative Book search engine using collaborative filtering, which provides users a personalized search experience for any type of book hunting intent query.
In this project, I built a content-based filtering recommendation system using Spotify playlists data from scratch. This involves the procedure of feature preprocessing, feature generation, recommendation modeling and application developement in Flask.
Implemented algorithms like Star cubing, Bayesian Classifier, FP growth, Decision Tree Induction, Logistic Regression, KNN from scratch without using any inbuilt library (like Scikit-Learn) with average accuracy of 90%.
Built a tool that flexibly generates hardware to accelerate the evaluation of multiple layers of convolution system with a non-linear function called a ReLU after each convolution. Designed it using digital system design techniques