rserran

bayesrules

R package for Supplemental Materials for the Bayes Rules! Book

courses

Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1

data-science-ipython-notebooks

Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

datasciencectacontent

repository for Community Mentor content related to the Johns Hopkins University Data Science Specialization on Coursera

Datasets

Machine learning datasets used in tutorials on MachineLearningMastery.com

dlookr

Tools for Data Diagnosis, Exploration, Transformation

EveningOfPythonCoding

This page contains information on the Evening of Python coding held in Austin

fpp3_exercises

Foreacasting:Principles and Practice (3rd ed.)

ggstatsplot

Collection of functions to enhance ggplot2 plots with results from statistical tests.

pdf-dump

A dump of all the data science materials (mostly pdf's) that I have accumulated over the years

rserran/pyod

A Python Toolbox for Scalable Outlier Detection (Anomaly Detection)

rserran/xgboost

Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Flink and DataFlow

rserran/bayestestR

:ghost: Utilities for analyzing Bayesian models and posterior distributions

rserran/bookclub-ema

rserran/bookclub-mshiny

Mastering Shiny Book Club

rserran/darts

A python library for user-friendly forecasting and anomaly detection on time series.

rserran/data.table

R's data.table package extends data.frame:

rserran/ema_ch_21

Explanatory Model Analysis Chapter 21

rserran/free_r_tips

Free R-Tips is a FREE Newsletter provided by Business Science. It comes with bite-sized code tutorials every week.

rserran/generative_ai_with_langchain

Build large language model (LLM) apps with Python, ChatGPT and other models. This is the companion repository for the book on generative AI with LangChain.

rserran/giskard

The testing framework dedicated to ML models, from tabular to LLMs 🛡️🧑‍🔬

rserran/handson-ml3

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

rserran/ISLP

ISLP package: data and code for labs

rserran/klib

Easy to use Python library of customized functions for cleaning and analyzing data.

rserran/lifelines

Survival analysis in Python

rserran/LightGBM

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

rserran/llama_parse

Parse files for optimal RAG

rserran/pycaret

An open-source, low-code machine learning library in Python

rserran/resources

PyMC3 educational resources

rserran/scikit-learn

scikit-learn: machine learning in Python

rserran/scikit-survival

Survival analysis built on top of scikit-learn

rserran/seaborn

Statistical data visualization using matplotlib

rserran/sktime

A unified framework for machine learning with time series

rserran/solve-any-data-analysis-problem

Accompanying data and code for Solve Any Data Analysis Problem (Manning, 2024)

rserran/statsforecast

Lightning ⚡️ fast forecasting with statistical and econometric models.

rserran/sunday-quant-scientist

A Free Newsletter for Quantitative and Algorithmic Trading, Portfolio Analysis, and Investing

rserran/ThinkBayes2

Text and code for the forthcoming second edition of Think Bayes, by Allen Downey.

rserran/tidy-text-mining

Manuscript of the book "Tidy Text Mining with R" by Julia Silge and David Robinson

rserran/time-series-analysis

Collection of notebooks for time series analysis

rserran/ultimate-python

Ultimate Python study guide for newcomers and professionals alike. :snake: :snake: :snake: