EbookMLCB - ebook Machine Learning cơ bản

Overview

Mã nguồn cuốn ebook "Machine Learning cơ bản", Vũ Hữu Tiệp.

ebook Machine Learning cơ bản pdf-black_white, pdf-color.

Mọi hình thức sao chép, in ấn đều cần được sự đồng ý của tác giả. Mọi chia sẻ đều cần được dẫn nguồn tới https://github.com/tiepvupsu/ebookMLCB hoặc https://machinelearningcoban.com.

Hiện sách giấy không còn được bán nữa.

Nếu bạn gặp bất cứ lỗi nào hoặc cho rằng nội dung có thể được cải thiện, bạn có thể tạo một issue tại đây.

Click Star nếu bạn thấy nội dung cuốn sách có ích. Cảm ơn bạn.

Owner
Machine Learning Engineer at Google
Python package for stacking (machine learning technique)

vecstack Python package for stacking (stacked generalization) featuring lightweight functional API and fully compatible scikit-learn API Convenient wa

Igor Ivanov 671 Dec 25, 2022
AI and Machine Learning with Kubeflow, Amazon EKS, and SageMaker

Data Science on AWS - O'Reilly Book Get the book on Amazon.com Book Outline Quick Start Workshop (4-hours) In this quick start hands-on workshop, you

Data Science on AWS 2.8k Jan 03, 2023
Built various Machine Learning algorithms (Logistic Regression, Random Forest, KNN, Gradient Boosting and XGBoost. etc)

Built various Machine Learning algorithms (Logistic Regression, Random Forest, KNN, Gradient Boosting and XGBoost. etc). Structured a custom ensemble model and a neural network. Found a outperformed

Chris Yuan 1 Feb 06, 2022
LibRerank is a toolkit for re-ranking algorithms. There are a number of re-ranking algorithms, such as PRM, DLCM, GSF, miDNN, SetRank, EGRerank, Seq2Slate.

LibRerank LibRerank is a toolkit for re-ranking algorithms. There are a number of re-ranking algorithms, such as PRM, DLCM, GSF, miDNN, SetRank, EGRer

126 Dec 28, 2022
Data from "Datamodels: Predicting Predictions with Training Data"

Data from "Datamodels: Predicting Predictions with Training Data" Here we provid

Madry Lab 51 Dec 09, 2022
Timeseries analysis for neuroscience data

=================================================== Nitime: timeseries analysis for neuroscience data ===============================================

NIPY developers 212 Dec 09, 2022
Decision tree is the most powerful and popular tool for classification and prediction

Diabetes Prediction Using Decision Tree Introduction Decision tree is the most powerful and popular tool for classification and prediction. A Decision

Arjun U 1 Jan 23, 2022
fastFM: A Library for Factorization Machines

Citing fastFM The library fastFM is an academic project. The time and resources spent developing fastFM are therefore justified by the number of citat

1k Dec 24, 2022
jaxfg - Factor graph-based nonlinear optimization library for JAX.

Factor graphs + nonlinear optimization in JAX

Brent Yi 134 Dec 21, 2022
XManager: A framework for managing machine learning experiments 🧑‍🔬

XManager is a platform for packaging, running and keeping track of machine learning experiments. It currently enables one to launch experiments locally or on Google Cloud Platform (GCP). Interaction

DeepMind 620 Dec 27, 2022
PySpark + Scikit-learn = Sparkit-learn

Sparkit-learn PySpark + Scikit-learn = Sparkit-learn GitHub: https://github.com/lensacom/sparkit-learn About Sparkit-learn aims to provide scikit-lear

Lensa 1.1k Jan 04, 2023
XAI - An eXplainability toolbox for machine learning

XAI - An eXplainability toolbox for machine learning XAI is a Machine Learning library that is designed with AI explainability in its core. XAI contai

The Institute for Ethical Machine Learning 875 Dec 27, 2022
Official code for HH-VAEM

HH-VAEM This repository contains the official Pytorch implementation of the Hierarchical Hamiltonian VAE for Mixed-type Data (HH-VAEM) model and the s

Ignacio Peis 8 Nov 30, 2022
Combines MLflow with a database (PostgreSQL) and a reverse proxy (NGINX) into a multi-container Docker application

Combines MLflow with a database (PostgreSQL) and a reverse proxy (NGINX) into a multi-container Docker application (with docker-compose).

Philip May 2 Dec 03, 2021
Nevergrad - A gradient-free optimization platform

Nevergrad - A gradient-free optimization platform nevergrad is a Python 3.6+ library. It can be installed with: pip install nevergrad More installati

Meta Research 3.4k Jan 08, 2023
vortex particles for simulating smoke in 2d

vortex-particles-method-2d vortex particles for simulating smoke in 2d -vortexparticles_s

12 Aug 23, 2022
30 Days Of Machine Learning Using Pytorch

Objective of the repository is to learn and build machine learning models using Pytorch. 30DaysofML Using Pytorch

Mayur 119 Nov 24, 2022
ML Optimizers from scratch using JAX

Toy implementations of some popular ML optimizers using Python/JAX

Shreyansh Singh 38 Jul 29, 2022
To design and implement the Identification of Iris Flower species using machine learning using Python and the tool Scikit-Learn.

To design and implement the Identification of Iris Flower species using machine learning using Python and the tool Scikit-Learn.

Astitva Veer Garg 1 Jan 11, 2022
Iris-Heroku - Putting a Machine Learning Model into Production with Flask and Heroku

Puesta en Producción de un modelo de aprendizaje automático con Flask y Heroku L

Jesùs Guillen 1 Jun 03, 2022