Ajit Sharad Mane's repositories
Bike-Sharing-Demand-Prediction-ML-Regression
This project aims to build a predictive model that could predict the number of rental bikes required for each hour using the Seoul Bike Sharing dataset. Linear regression, Lasso (L1), Ridge (L2), ElasticNet, Decision Tree, Random Forest, and XGBoost algorithms are used to build a model to predict the number of rental bikes required for each hour.
Python-Practice
This repository serves as a practice ground for Python programming in the context of data science. It encompasses a collection of code snippets and exercises aimed at enhancing Python skills specifically tailored for data analysis, machine learning, and data visualization.
EDA-Hotel-Booking-Analysis
Conducted exploratory data analysis on the provided dataset and derived valuable conclusions about broad hotel booking trends and how various factors interact to affect hotel bookings. Created dashboard using Tableau.
Bank-Marketing-Effectiveness-Prediction-ML-Classification
This project focuses on utilising machine learning techniques to predict the effectiveness of bank marketing campaign. Logistic Regression, Decision Tree, Random Forest, Gradient Boosting Machine, XGBoost, K Nearest Neighbor, Naive Bayes, Support Vector Machine, and Artificial Neaural Networks algorithms are used to build a model for prediction.
Data-Wrangling-Using-Pyspark-for-Video-Games-Datasets
The objective was to complete data engineering task for IndiGG interview using pyspark. Includes dataset download, processing, analysis using Python, Spark, AWS Glue, Lambda, Step Functions, and SQL.
Netflix-Movies-and-Tv-Shows-Clustering-ML-Unsupervised
The Netflix Movies and TV Shows Clustering Project aims to cluster similar movies and TV shows available on Netflix into different clusters based on their content. The project uses Natural Language Processing (NLP) and unsupervised machine learning techniques to analyze the dataset, including K-Means, Hierarchical clustering, and DBSCAN algorithms.
Python-Advanced-Data-Wrangling-Practice
Python Advanced Data Wrangling Practice repository offers comprehensive resources and examples for mastering advanced data manipulation techniques using Python.
Spam-Ham-Detection-Bert-Tensorflow--Deep-Learning
Email spam/ham detection using BERT & TensorFlow. Implementing DL model to classify emails based on content. Includes BERT fine-tuning, training scripts, evaluation metrics, and dataset preprocessing.
Cat-vs-Dog-Popularity-Dashboard-Using-Power-Bi
This repository contains a dashboard created in Power BI to visualize the popularity of cats and dogs in the United States. The dashboard provides insights and analysis based on the available data.
End-to-End-Student-Math-Score-Prediction-with-Deployment
End-to-end project predicting students' math scores, covering data ingestion, transformation, model training, and deployment. Uses Conda, Git, MySQL, DVC, MLflow, Dagshub, Flask, AWS CodePipeline, and Elastic Beanstalk. Includes data processing and model management scripts with generated artifacts.
Kevin_Cookies-Analytics-Report-Dashboard
This repository houses a Power BI dashboard that provides comprehensive insights into the performance and key metrics of the Kevin Cookies Company. Analyze sales, inventory, customer engagement, and profitability data through interactive visualizations. Gain valuable business insights and make data-driven decisions.
Stock-Price-Prediction-And-Forecasting-Using-Stacked-LSTM--Deep-Learning
This repository features a deep learning project that forecasts Apple Inc. (AAPL) stock prices using historical data. It includes data preprocessing, training of an LSTM model, and predicting future stock prices. The results are visualized to show both historical and predicted values.
Diabetes-Prediction-Deep-Learning-Model
A machine learning model for predicting diabetes risk using key health indicators. The project involves data preprocessing, model development with TensorFlow and scikit-learn, and evaluation to achieve accurate predictions.
hospitality-data-insights-and-cancellation-prediction-model
This repository provides a comprehensive analysis and predictive modeling solution for hospitality data, focusing on booking cancellations. The project aims to derive actionable insights from historical hotel booking data and build a robust machine learning model to predict whether a customer will cancel their booking.
Python-Notes
This repository contains a comprehensive set of notes and examples for Python programming language. The notes cover various topics ranging from basic syntax and data structures to advanced concepts such as object-oriented programming, and data science. This repository is a valuable resource for learning and mastering Python.
Real-Time-Image-Segmentation-And-Object-Detection-Using-Pixellib
This repository showcases a real-time image segmentation and object detection project utilizing the PixelLib library. The project aims to implement and demonstrate advanced computer vision techniques for accurately identifying and segmenting objects in images and video streams.
SQL-Notes
This repository include notes on SQL syntax, examples of SQL queries, best practices for database design, and other useful information for SQL developers and database administrators. In addition to providing a valuable resource for SQL learners and practitioners, a GitHub repository for SQL notes can also foster a community of contributors.