raqibcodes's Projects
A list of 99 machine learning projects for anyone interested to learn from coding and building projects
Config files for my GitHub profile.
Here is the proposed solution to the "Prediction of customer personality analysis" problem
This project involves creating an animated GIF maker using Streamlit. The web application allows users to upload a set of images and convert them into an animated GIF with custom animation settings. The purpose of the project is to provide an easy-to-use tool for creating animated GIFs for personal or professional use.
A repository for the source code, notebooks, data, files, and other assets used in the data science and machine learning articles on LearnDataSci
A simple Audio Transcription Web-App
The aim of this project is to perform sentiment analysis on Twitter data related to customer satisfaction with Nigerian banks, in order to gain insights into customer opinions and experiences and identify areas for improvement in the banking industry.
This Application is a book recommender system uses a content-based approach, leveraging book features to recommend similar books to users based on features of the books or characteristics of the items and the user's preferences.
I will be analyzing one of the longest running conflicts in the world here, the war between Israel and Palestine and then finish up by building a detailed Dashboard using Matplotlib.
This project is the first case study of the Google Data Analytics Capstone, in which I used data analytics to help drive informed decision making for a bike-share company seeking to maximize profits and generate more revenue. The analysis included data cleaning, exploratory data analysis, and statistical modeling to identify key trends and patterns
This web app is a sentiment analysis tool developed by raqibcodes. It has the capability of detecting whether user-entered text has an underlying Positive, Neutral or Negative sentiment. The text classification model was trained on Feedback survey data collected from 300 level Undergraduate Computer Engineering Students at the University of Ilorin
This repository has been created as part of the kaggleXBIPOC Mentorship Program. The aim of this project is to establish the sentiment association between the various cryptocurrencies like Bitcoin, Ether using real time twitter data and RoBERTa Model for classification .
Decoding Customer Insights: Unsupervised Learning for Dynamic Segmentation. This analysis enables businesses to tailor their products and services to different customer segments, rather than using a generic approach. By using techniques like unsupervised learning, companies can uncover valuable insights about customer needs, behaviors, and concerns
My First App created using Flask and deployed on Heroku
This project involves scraping data from the La Liga football league website using Python's Beautiful Soup library. The scraped data includes player statistics, team rankings, and other key metrics related to the league. The purpose of the project is to gather data for further analysis and gain insights into player and team performance.
Repository containing my Generative AI and RAG projects
The assignment and my solution to the IBM Data Science Specialization's course 5 - Python project for data science
The Unified Machine Learning Framework
Download and Activate Microsoft Office 2021 (Latest) for free. (Legal)
Simplify code execution with Open Interpreter UI Project with Streamlit. A user-friendly GUI for Python, JavaScript, and more. Pay-as-you-go, no subscriptions. Ideal for beginners.
This project explores the features related to borrowers and how it relates to the loans they took from Prosper, a US loan company
Sentiment analysis of student feedback in engineering education. The goal is to analyze and gain insights from student feedback data to understand their sentiments and identify areas for improvement. The sentiment analysis is performed using natural language processing techniques and machine learning algorithms to classify feedback data.
This project involves analyzing soccer data from different datasets using SQL and Python. The analysis includes data wrangling and cleaning, querying the data with SQL to extract relevant information, and performing additional analyses using Python. The project provides a better understanding of the patterns and trends in soccer data.
This project uses machine learning to predict customer churn in a telecom industry. By analyzing customer demographics, usage patterns, and churn status, I built a model that accurately predicts which customers are at risk of churning
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent