Jinu Nyachhyon's Projects
Data Analysis and Visualization of dataset containing Novel Prize Winners and concluding certain facts based on the outputs.
Chatverse is a platform where people from around the world can create or participate in various rooms on the topics they are most interested in and meet like-minded people.
This research compares the capabilities of four distinct CNN models for the task of classifying medical images: SimpleCNN, LeNet5, AlexNet, and VGG16. The study looks into which CNN model does this task the best and offers insights into the variables that affect the model's performance.
This is a final project for Code in Place 2021, offered by Stanford University. The code is for a Caterpillar Game.
Course developed by Daniel Gakwaya. Reference from:
Customizing default admin page provided by django.
Learned Dart programming language and implemented them via few challenges implemented in flutter.
The roadmap to data scientist track in Datacamp have number of exercises and such notebooks are curated here.
A comprehensive introduction to machine learning in Python including how to process data for features, train your models, assess performance, and tune parameters for better performance. Also introduction to natural language processing, image processing, and popular Python machine learning packages such as scikit-learn, Spark, and Keras.
Prediction of provided 'Text Abstracts' that belongs into various categories along with their category number using Machine Learning Algorithms such as Naive Bayes, Logistic Regression and Linear SVM.
Mini Bootcamp for Data Science; that include learning python libraries such as Pandas, Numpy and Matplotlib and finally moving to NLP.
Our model predicts binding affinity across a diverse set of drugs and target groups. Drug-target interaction prediction task aims to predict the interaction activity score in silico given only the accessible compound structural information and protein amino acid sequence.
Hacker statistics to calculate your chances of winning a bet. Use random number generators, loops, and Matplotlib to gain a competitive edge!
An interface for user and guide to connect with recommendation system and a built in chatbox.
Investigating Netflix Movies and Guest Stars in The Office
Landing Page designed using HTML and CSS. New features are on the way..
Learn It is a dynamic web app powered by OpenAI and Whisper API. It effortlessly summarizes videos and PDFs, offering concise insights. With AI Q&A, it's your shortcut to understanding multimedia content. Transcribe, summarize, and ask questions to unravel knowledge swiftly.
Implementing various segmentation architectures for medical image segmentation. This repo currently implements the popular UNet for liver segmentation.
Paper replication on Medical Image Segmentation Using Squeeze-and-Expansion Transformers
Sales Prediction of 10 different stores having 50 items each using machine learning algorithms such as Light GBM, Linear Regression, XGBoost and CatBoost; also comparative analysis on all the ML algorithms used.
This repository serves as a comprehensive guide through the evolution of Natural Language Processing (NLP), starting from foundational principles and classical approaches, gradually transitioning to Deep Learning techniques, and culminating in an in-depth exploration of Transformer models.
This repo has basics of OpenCV(reading images and videos, image transformations) to more advanced concepts (color spaces, edge detection). Also includes building a Deep Computer Vision model to classify between the characters in the popular TV series "The Simpsons".
This repo contains notebooks that works with challenging data, including date and time data, text data, and web data using APIs. It also contains unit testing and concepts of OOP in Python. The notebooks uses Python libraries, NumPy, pytest, and pycodestyle, that will helps in tasks such as web development, data analysis, and task automation.
Building a projection of the business potential for each of the 4000 regions for the next 15 months using time series forecasting techniques.
In this notebook, there is a comprehensive analysis of the Android app market by comparing over ten thousand apps in Google Play across different categories. Insights in the data to devise strategies to drive growth and retention.