Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field is closely related to artificial intelligence and computational statistics.
This repository consist of machine learning models which can be use for predicting the future instance. More specifically this repository is a Machine Learning course for those who are interested in learning the basics of machine learning algorithms.
This Repository Contains all the Information and the Projects that I did at SAIL during my Internship
S.O.L.I.D. Principles for Machine Learning project.
Analyzing and predicting Google's stock prices through detailed data exploration and advanced LSTM models. This project involves data preprocessing, creating time-series sequences, constructing and training LSTM networks, and evaluating their performance to forecast future stock prices utilizing Python and Machine Learning libraries.
Google Cloud Platform (GCP) Guide. Learn all about Google Cloud Tools, Services, and Certifications.
Data Analysis, training Machine Learning models, and Model Evaluation and Refinement for AutoMobiles dataset.
Linear Prediction Model with Automated Feature Engineering and Selection Capabilities
Factoid Question Answering System - An advanced Open-domain Question Answering (ODQA) project that automatically answers factoid questions in Arabic and English languages using NLP and machine learning techniques
🚀Absolutely! Let's dive deeper into the collection of Machine Learning projects I completed during my immersive 1-month virtual internship at CodeAlpha.
Fraud Detection Model Access via API
Real-Time Financial Advisor using LLMs - Design, develop, deploy on production-grade ML applications.
A package that makes it trivial to create and evaluate machine learning pipeline architectures.
This repository contains the projects I worked on during my Codsoft internship. Each project focuses on a different machine learning problem, including credit card fraud detection, customer churn prediction, movie genre classification, and SMS spam detection.
MLModelScope is an open source, extensible, and customizable platform to facilitate evaluation and measurement of ML models within AI pipelines.
Streamlit web application for visualizing data and presenting the predictions of a trained machine learning model.
Elevate Your Skills with Comprehensive Machine Learning Tutorials.
Agent Based Software Engineering Semester Project in python: Heart Disease Prediction . Complete User Interface along MYSQL database connection to store data .
Data Analysis, training Machine Learning models, and Model Evaluation and Refinement for LaptopPricing dataset.
Data-Acquisition and Basic Insights, Data Wrangling, Exploratory Data Analysis (EDA), and Training Prediction Models(Machine Learning) on two datasets.
An AI model for detecting abnormal transactions in banking data.