Data preprocessing for Artificial Intelligence
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Updated
Jun 1, 2024 - Jupyter Notebook
Data preprocessing for Artificial Intelligence
Rock Paper Scissors is a zero sum game that is usually played by two people using their hands and no tools. The idea is to make shapes with an outstretched hand where each shape will have a certain degree of power and will lead to an outcome.
Complete resources of Machine Learning concepts in ipynb Files working on Google Colab
Welcome to the Machine Learning Detection Sound project! This project harnesses the power of machine learning to analyze car sounds, enabling the detection of vehicles based on their audio signatures.
Using linear regression machine learning model to predict home prices.
Underwater image enhancement using image sharpening methods on google colab
This code explores the Sleep Health and Lifestyle dataset, performing data loading, preprocessing, and visualization tasks. It analyzes relationships between variables like sleep duration, physical activity, gender, occupation, and BMI using scatter plots, box plots, etc.
This repository contains a Python implementation of a Multiple Linear Regression model to predict a company's profit based on various expenditures and the company's state.
Projeto de análise de dados (validação de hipóteses)
Emotion classification base on short texts
This linear regression model aims to predict an individual's salary based on their years of experience.
This repo contains the notebook python code to run Ollama on Google Colab with Ngrok and Gradio as ChatBot with Memory and Verbose generation
This repo contains a code that uses colabxterm and langchain community packages to install Ollama on Google Colab free tier T4 and pulls a model from Ollama and chats with it
Bu proje çalışmasında Türkiye İstatistik Kurumu’ndan alınan 1927-2000 yılları arası genel nüfus sayımı sonuçları ve 2007-2022 arası adrese dayalı nüfus kayıt sistemi sonuçları veri seti olarak alınarak keşifsel veri analizi yapılmıştır.
EfficientNetV2 (Efficientnetv2-b2) and quantization int8 and fp32 (QAT and PTQ) on CK+ dataset . fine-tuning, augmentation, solving imbalanced dataset, etc.
Helmet Detection using tiny-yolo-v3 by training using your own dataset and testing the results in the google colaboratory.
Supervised-method--Decision-trees--algorithms-Diabetes-prediction if either one has diabetes or not
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