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.
Repository for my practice files and notes following Krish Naik's "100 Days of ML" YouTube playlist. This repo includes Jupyter notebooks and datasets organized by day, documenting my learning journey in machine learning.
This repository contains a Jupyter notebook for building an anime recommendation system using various machine learning models. The notebook includes steps for data preprocessing, feature extraction, model training, and creating a user-friendly graphical user interface (GUI) with tkinter.
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
This repository contains a collection of machine learning examples implemented in Jupyter Notebooks. Each notebook demonstrates a different machine learning technique or algorithm, along with explanations and code examples.
Educational notebooks reviewing machine learning models and concepts.
Some random stuff
Loan Eligibility Prediction Model: A machine learning application to predict loan approval based on applicant data. Includes a web interface for submitting loan applications and receiving predictions. Built with Python and Jupyter Notebook.
Exploring Python-based projects
This repository is meant to store the code examples used in articles posted on www.insidelearningmachines.com. Each article on the website will have an associated jupyter notebook here with the same name.
In this notebook, I have done Data Cleaning, Data Wrangling, EDA and Feature Engineering. After that I trained the dataset using Machine Learning Algorithm Random Forest Regressor.
It contains a jupyter notebook which discusses about different survival rates on the basis of gender, class etc.
This repository serves as a notebook for Data Science studies. It contains text files with core concepts, and code for implementation of those concepts.
Bunch of notebooks collection from Kaggle competitions.
This repository contains a collection of Jupyter Notebooks for conducting Exploratory Data Analysis (EDA) and Statistical Analysis on various datasets.
This Repository contains the Machine Learning Algorithms! These collection of Jupyter notebooks showcasing various machine learning algorithms implemented in Python using Scikit-learn library.
Collection of Notebooks in Google Colab directly usable for study activities
This repository is a hub for data science enthusiasts, offering a diverse collection of projects, notebooks, and resources covering topics such as data analysis, machine learning, deep learning, and generative AI. Explore innovative ideas, contribute to cutting-edge research, and enhance your skills in the dynamic field of data science
🔍 Dive into Machine Learning with this collection of Google Colab notebooks. 📚 From beginners to pros, explore algorithms, datasets, and practical skills. 🚀 Start your ML journey here! 💡
Jupyter notebooks for practicing Python data analysis and visualization with Matplotlib, NumPy, Pandas, SciPy, and Seaborn.
This repository contains mini projects in machine learning in deep learing with notebook files