Repository containing portfolio of data science projects completed by me for academic, self learning, and hobby purposes. Presented in the form of iPython Notebooks, and R markdown files (published at RPubs).
For a more visually pleasant experience for browsing the portfolio, check out [[email protected]]
-
[Netflix Movie Recommendation](https://github.com/gujralsanyam22/data-science-portfolio/blob/master/Netflix_Movie Prediction/Movie_recommendation.ipynb):
A model to predict the o help customers find those movies, they developed world-class movie recommendation system: CinematchSM. Its job is to predict whether someone will enjoy a movie based on how much they liked or disliked other movies. Netflix use those predictions to make personal movie recommendations based on each customer’s unique tastes.
**Build a recommender system from scratch
1.) Online recommendation systems are the in thing to do for many e-commerce websites. A recommendation system broadly recommends products to customers best suited to their tastes and traits.
2.) Building recommender systems today requires specialized expertise in analytics, machine learning and software engineering, and learning new skills and tools is difficult and time-consuming.
- Loan Price Prediction: Our aim from the project is to make use of pandas, matplotlib, & seaborn libraries from python to extract insights from the data and xgboost, & scikit-learn libraries for machine learning.
Secondly, to learn how to hypertune the parameters using grid search cross validation for the xgboost machine learning model.
And in the end, to predict whether the loan applicant can replay the loan or not using voting ensembling techniques of combining the predictions from multiple machine learning algorithms.
-
WINE-QUALITY PRICE PREDICTION: Predicting the Quality of Red Wine using Machine Learning Algorithms for Regression Analysis, Data Visualizations and Data Analysis.
-
Hand-Written Digit Recognition: Designing and implementing a Convolutional Neural Network that learns to recognize sequences of digits using synthetic data generated by concatenating images from MNIST.
Handwritten Digit Recognition using Convolutional Neural Networks in Python with Keras.
_Tools: scikit-learn, Pandas, Seaborn, Matplotlib, Pygame_
-
- 3-way Sentiment Analysis for Tweets: 3-way polarity (positive, negative, neutral) classification system for tweets, without using NLTK's sentiment analysis engine.
Tools: NLTK, scikit
-
- Python
- Scalable Walkability Analysis of Melbourne: Analysis of walkability of suburbs in Melbourne, Victoria and its implications.
- Titanic Dataset - Exploratory Analysis: Exploratory Analysis of the passengers onboard RMS Titanic using Pandas and Seaborn visualisations.
- Stock Market Analysis for Tech Stocks: Analysis of technology stocks including change in price over time, daily returns, and stock behaviour prediction.
- 2016 US General Election Poll Data Analysis: Very simple analysis of 2016 US General Election Poll data.
- 911 Calls - Exploratory Analysis: Exploratory Data Analysis of the 911 calls dataset hosted on Kaggle. Demonstrates extraction of useful features from different variables.
Tools: Pandas, Folium, Seaborn and Matplotlib
- Python
-
-
Python
- [ML with Tkinter](https://github.com/gujralsanyam22/data-science-portfolio/blob/master/ML%20Micro%20Projects/Machine%20Learning%20with%20 trading_analysis_project_w_tkinter.py): Using tkinter to predict which trade is increase day by day .
-
ML with K Nearest Neighbours and keras: Using KNN and keras to classify instances The early detection of skin cancer is crucial, the estimated 5-year survival rate for patients whose melanoma is detected early is about 98 percent in the U.S. The survival rate falls to 62 percent when the disease reaches the lymph nodes, and 18 percent when the disease metastasizes to distant organs(Cancer Facts and Figures 2017. American Cancer Society. Accessed January 10, 2017.). According to a recent report from the World Bank(World development report 2016 digital dividends.), "The poorest households are more likely to have access to mobile phones than to toilets or clean water,". An smart phone app that detects skin cancer could potentially reach people that don't have easy access to health-care services.
-
Python with pygame: A Snakes and Ladders Game made with Python 3.7 using module pygame.
-
I also dabble in all other kinds of technology. You can find a general portfolio here.
If you liked what you saw, want to have a chat with me about the portfolio, work opportunities, or collaboration, shoot an email at contact [email protected]