The Learn R Through Examples by Xijin Ge, Jianli Qi, and Rong Fan provides an introduction to data analysis with R. The book covers the core topics of data analysis using different datasets, from simple and clean datasets to messy and big datasets. π§΅ππΌ
Hands-on Data Science: Complete your First Project π
This beginner crash course by Misra Turp provides an introduction to the foundations of data science by solving real-life examples. This includes the different steps of a data science project, from setting the environment to loading and analyzing the data using Python, git, Jupyter notebooks and other tools ππΌ
This week, PyMC version v5.13.0 was released. PyMC is one of the main #Python π libraries for πππ²ππ¬π’ππ§ statistics β€οΈ. It provides a framework for probabilistic programming, enabling users to build #Bayesian models with a simple Python API and fit them using πππ«π€π¨π― ππ‘ππ’π§ ππ¨π§ππ πππ«π₯π¨ (MCMC) methods π.
The new release includes new features, bug fixes π, and documentation improvements π. More details on the release notes π π #DataScience#machinelearning#statistics
R programmers in The Netherlands, you may be interested in this event with Jenny Bryan about R package development. It is an honour to have her in Utrecht so I hope more people can benefit from this in person opportunity!
(1/2) Models Demystified - A Practical Guide from t-tests to Deep Learning πππΌ
The Models Demystified is a new book by Michael Clark and Seth Berry that focuses on the mechanizing of core data science algorithms. That includes the following topics:
β Linear and logistic regression
β Generalized Linear Models
β Regularization methods
β Model training approaches
β Deep learning and neural networks
β Causal Modeling
Looking to do some data filtering in base R? Well then of course I have a post for you! Many times people in a corporate environment are strapped from installing packages or it is cumbersome to get it done, this is why I like to focus on base R solutions.
π¦ Build and cache R packages with Nix @brodriguesco
π Latest webR improvements in 0.3.1 @gws@Posit
π¬ Visualizing dplyr operations @andrew
Spreading the word of the RWeekly project, contributing your favorite resource to the site, or sending your hosts a fun boost are excellent ways to participate in #value4value!
The Bandit Algorithms by Tor Lattimore and Prof. Csaba SzepesvΒ΄ari provides an introduction to the multi-armed bandit problem. This includes different approaches for solving this type of problems using stochastic, adversarial, and Bayesian frameworks.
Hello #Mastodon! I'm a former practicing lawyer and professor. Looking to chat about #legal issues, #datascience (especially computational text analysis using Python and R π ), and #travelphotography. I care a lot about equitable access to the court system for all peoples, including those who are #neurodiverse, in the US by way of #immigration, #black or people of color.
Production Monitoring & Automations of LLM with LangSmith π¦ππΌ
LangChain released a crash course for LangSmith, their DevOps platform for deploying LLM applications into production. The course covers topics such as:
β LLM applications monitoring
β Setting automation
β Performance monitoring