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Data Science, Machine Learning, Deep Learning, NLP, Python & Library's cheat Sheet - Interview Questions & Notes
线性回归;病态线性回归;聚类分析; 主成分分析 ; 多目标决策
An algorithm intended to predict the yield of any crop. Used Agricultural Data sets for building the Step-wise Regression Model. Technology Stack: R language, SQL, Linear Regression library, Plumber library, Swagger API
This is all Data Science Assignments Files. I am currently working on it, so you may not find some files here.
:chart_with_upwards_trend: :currency_exchange: Linear Regression Forecasting Exchange Rates
I have applied the fundamental idea of Linear Regression with Single Variable input. I implemented the Gradian Descent algorithm simply from scratch with no libraries such as Scikit-Learn. I just used NumPy.
Codes and Project for Machine Learning
Tutorials of Machine Learning in Jupyter Notebooks
This repository contains many machine learning topics and projects
Machine learning Basics. Just Started learning and uploading small chunk of codes and small projects .
Data visualisation using seaborn
ML projects, which I worked on utilising different machine learning algorithms.
The second project in SDAIA T5 bootcamp
EDA analysis and a couple of models from classical machine learning on actual data as of 12.07.2023 about video games. Dataset from kaggle link in readme.
Notebooks explaining various Machine Learning concepts.
Analyzing prototype suspension coils data for production troubles.
Data Analysis and Machine Learning Projects
Here the basic of the the Linear regression problem .
Simple salary prediction using machine learning models.
This classifier web app basically developed using Streamlit (Python - framework) and it classifies the categories of "Diabetic" or "Not Diabetic" based on certain input parameters. In this app, we can choose different classifiers like; SVM, RandomForest, GridSearch, Logistics Regression, for the classification.
An app which can predict the prices of house based on training data and certain input parameters, deployed on Heroku.
DASS (Depression Anxiety Stress Scales) Prediction using IBM SPSS Modeler (Methodology - CRISP DM)
Stock price prediction is a crucial aspect of financial markets, involving the use of mathematical models and machine learning techniques to forecast the future price movements of stocks or financial assets.
A basic model using Linear Regression to predict car price
The project aims to provide valuable insights for fair compensation strategies and improved logistical planning.
Diabetes prediction
🏠 this machine learning problem aims to predict the price of houses in Boston
Regression is one of the foundational techniques in Machine Learning. Being one of the most well-understood algorithms, beginners always struggle to understand some fundamental terminology related to regression. In this series of projects, I will try to give you basic ideas of underlying concepts with the help of practical examples. If you are starting your career or want to brush up on your knowledge of regression, this repo is made up for you. These projects begins by introducing some simple real-life examples for regression. From a brief introduction to most of the concepts used in regression to hands-on experience, these projects will give you enough understanding to apply those in real-world problems. With the help of the background developed, you will code your regression model in python.
Statistical analysis of MechaCar vehicles and a study designed to compare the MechaCar vehicles to competitors.
Predicting Titanic survival using machine learning models with age, sex, ticket class, and fare. Tested linear regression, logistic regression, and KNN with cross-validation and metrics like accuracy and recall. The best-performing model is available on GitHub with code, data, and results.