Efficient R programming
There are many excellent R resources for visualization, data science, and package development. Hundreds of scattered vignettes, web pages, and forums explain how to use R in particular domains. But little has been written on how to simply make R work effectively-until now.
Deep Learning or Machine Learning? (MathWorks)
“In this ebook, we discuss some of the key differences between deep learning and traditional machine learning approaches. We look at three factors that might influence your decision and then step through an example that combines the two approaches”. (MathWorks).
Artificial Intelligence use for help. The coronavirus R dataset package
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 in Society
“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)
Matriz de recursos de Deep Learning
El siguiente recurso describe los siguientes marcos:
TensorFlow
Theano
Cafe
MXNet
apache
SystemML (proyecto de incubadora)
BigDL
DistBelief
TPOT is a Python Automated Machine Learning tool
Consider TPOT your Data Science Assistant. TPOT is a Python Automated Machine Learning (AutoML) tool that optimizes machine learning pipelines using genetic programming.









