python 0基础入门机器学习

Você foi contratado por uma empresa de e-commerce que está buscando entender melhor o comportamento de seus clientes para personalizar as suas campanhas de marketing. Para isso, a empresa disponibilizou uma base de dados em csv contendo dados sobre clientes, produtos e transações da loja realizadas entre os anos de 2010 e 2011.

In this repository i am going work on multiple Classification models and technique's.

Technical Articles

Make a prediction to determine the price of each launch of a rocket, if the rocket can recover the first stage like SpaceX's Falcon 9.

GrocerySegmentAI is a platform as a service for grocery businesses. This product provides a way for these businesses to upload customer data and receive accurate predictions on which customers will buy a specific product on their next order.

This code does linear regression using scikit-learn and custom NumPy implementation. It loads datasets, removes NaNs, scales features, trains and evaluates models, and plots best fit line. Custom model uses gradient descent. Outputs R2 score, coefficients, and intercept.

CyberSight is our final project at Bar-Ilan University. The primary objective of the project is to identify whether a given picture of a human face is generated by artificial intelligence or depicts a real person.

This repo consists of hands-on ML experiments for learning purposes.

Research focuses on the use of Machine Learning algorithms to create and Intrusion Detection System(IDS) that is able to predict and categorize different types of network attacks.

This is a project that was completed while taking the Udemy course - Python for Machine Learning & Data Science Masterclass.

Machine Learning Course from Udemy

Ejemplos sobre las redes neuronales CNN, utilizando Python y sus librerias de ciencia de datos; así como: Keras, Tensorflow, Estimator API y Excel.

In this i tried to design a model that can predict the price of stock using different methods and algorithms.

Diabetes Prediction Web App

LeNet-5 Image Classification project demonstrates the power of the LeNet convolutional neural network for character and digit recognition in grayscale images.

ResNet-50, with 50 layers, excels in image classification by addressing the vanishing gradient problem. Skip connections facilitate seamless information flow, empowering the model for intricate feature learning. Its unique architecture makes ResNet-50 a robust choice for complex pattern recognition.

Basics of Machine Learnings 🧠 Notes on Topics, videos and resources with clean and concise examples to try 💡

Default_Prediction_for_Loan_Data

Support Vector Machines (SVM) are supervised learning models used for classification and regression analysis. They are particularly effective in high-dimensional spaces and situations where the number of dimensions exceeds the number of samples. SVMs are also memory efficient as they use a subset of training points called support vectors.