These data can be used in the area of artificial intelligence (machine learning and deeplearning) and among all obtain more efficient and faster results regarding coronavirus.
Artificial Intelligence use for help. The coronavirus R dataset package Leer más »
«The artificial intelligence (AI) landscape has evolved significantly from 1950 when Alan Turing first posed the question of whether machines can think. Today, AI is transforming societies and economies. It promises to generate productivity gains, improve well-being and help address global challenges, such as climate change, resource scarcity and health crises. Yet, as AI applications are adopted around the world, their use can raise questions and challenges related to human values, fairness, human determination, privacy, safety and accountability, among others. This report helps build a shared understanding of AI in the present and near-term by mapping the AI technical, economic, use case and policy landscape and identifying major public policy considerations. It is also intended to help co-ordination and consistency with discussions in other national and international fora». (OECD)
El objetivo de este documento es alentar a los investigadores de inteligencia artificial y diseñadores de productos a cambiar del pensamiento unidimensional sobre los niveles de automatización / autonomía a un nuevo marco HCAI bidimensional.
Inteligencia artificial centrada en el ser humano: confiable y segura Leer más »
Consider TPOT your Data Science Assistant. TPOT is a Python Automated Machine Learning (AutoML) tool that optimizes machine learning pipelines using genetic programming.
TPOT is a Python Automated Machine Learning tool Leer más »
C++ Notes for Professionals book is compiled from Stack Overflow Documentation,. 708 pages, published on May 2018
«H2O has been the driver for building models at scale. We are talking about billions of claims. You can’t do this with standard off the shelf open source techniques». (H2o.ai).
AutoML: a introduction tutorial about H2O Driverless AI Leer más »
A great selection of resources on learning deeplearning by Lex Fridman from the Massachusetts Institute of Technology (MIT).
Resources on learning deeplearning from the Massachusetts Institute of Technology Leer más »
The second edition of this best-selling Python book (100,000+ copies sold in print alone) uses Python 3 to teach even the technically uninclined how to write programs that do in minutes what would take hours to do by hand.
AUTOMATE THE BORING STUFF WITH PYTHON: PRACTICAL PROGRAMMING FOR TOTAL BEGINNERS Leer más »
Phyton’s most notable points are:
-Is a great library ecosystem (Scikit-learn, Pandas, Matplotlib, NLTK, Scikit-image, PyBrain, Caffe, StatsModels, TensorFlow, Keras, etc).
-Growing popularity.
-Has a low entry barrier, has flexibility, is a platform independence, has readability, good visualization options, good community support and growing popularity.
Machine learning in Python: the top programming language Leer más »
This LaTeX Notes for professionals book is compiled from Stack Overflow Documentation. (60 pages, published on May 2018)