Pinned Repositories
Algorithms
:computer: Data Structures and Algorithms in Python
An-Introduction-to-Statistical-Learning-with-Applications-in-R---python
An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code
arm
My solutions to the exercises in "Data Analysis Using Regression and Multilevel/Hierarchical Models" by Andrew Gelman and Jennifer Hill
at236x-deep-learning-explained
Workbooks for https://edX.org at236x course
awesome-courses
:books: List of awesome university courses for learning Computer Science!
Harvardx-PH526x
Solutions to Homework Exercises for Harvardx: PH526x Using Python for Research, EdX, Nov-Dec 2016
MITx-6.00.2x
Coding exercises, Problem Sets, and lecture code for MITx: 6.00.2x Introduction to Computational Thinking and Data Science, EdX, March-May 2017
mjimcua's Repositories
mjimcua/cs230-code-examples
Code examples in pyTorch and Tensorflow for CS230
mjimcua/deep-learning-with-python-notebooks
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
mjimcua/ds_utils
mjimcua/dt_snippets
mjimcua/Exploratory-Data-Analysis-with-Python
Exploratory Data Analysis with Python, Pandas, Numpy...
mjimcua/feature-engineering-book
Code repo for the book "Feature Engineering for Machine Learning," by Alice Zheng and Amanda Casari, O'Reilly 2018
mjimcua/feature_engineering_helpers
Helper functions to work with features
mjimcua/General_Handouts
mjimcua/LightGBM
A fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. It is under the umbrella of the DMTK(http://github.com/microsoft/dmtk) project of Microsoft.
mjimcua/logging_helpers
mjimcua/machine_learning_datasets
Machine Learning Datasets
mjimcua/mit-15-003-data-science-tools
Study guides for MIT's 15.003 Data Science Tools
mjimcua/mjimcua.github.io
About me
mjimcua/ml_helpers
Machine Learning helpers to create models
mjimcua/mlcourse.ai
Open Machine Learning Course
mjimcua/Principles-of-Machine-Learning-R
Principles of Machine Learning R
mjimcua/python-flask-api
mjimcua/python-snippets
mjimcua/PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks
mjimcua/reinforcement-learning
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
mjimcua/reinforcement-learning-an-introduction
Python implementation of Reinforcement Learning: An Introduction
mjimcua/Research-Methods-for-Data-Science-with-Python
Research Methods for Data Science with Python
mjimcua/spark
Mirror of Apache Spark
mjimcua/SQL_helpers
Functions to work with SQL Server from python
mjimcua/sql_server_course
mjimcua/stanford-cs-229-machine-learning
VIP cheatsheets for Stanford's CS 229 Machine Learning
mjimcua/UCAV
mjimcua/visualization_helpers
Visualization functions
mjimcua/XCS224N-Handouts
Contains Lecture Notes and Suggested Readings for XCS224N
mjimcua/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