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e2b : datascience   23

machinelearningmindset/machine-learning-course: Machine Learning Course with Python
:speech_balloon: Machine Learning Course with Python - machinelearningmindset/machine-learning-course
machinelearning  python  machine-learning  datascience  course  ml  tutorial  ai 
5 weeks ago by e2b
Quantitative Economics
This website presents a series of lectures on quantitative economic modeling, designed and written by Thomas J. Sargent and John Stachurski.
datascience  python  julia  math  econometrics  economics  finance  quantecon  quant 
february 2019 by e2b
Browse the State-of-the-Art in Machine Learning
579 leaderboards • 992 tasks • 744 datasets • 9515 papers with code.
machinelearning  ml  ai  papers  research  datascience 
february 2019 by e2b
Who is @horse_js?
A data science project to uncover the true identity of the notorious JavaScript parody account.
javascript  fun  humor  machinelearning  datascience  interesting  statistics  programming 
february 2019 by e2b
How to deliver on Machine Learning projects – Insight Data
Concrete tips for each phase of ML Development, as well as on optimizing the process as a whole.
programming  datascience  machine-learning  advice  machinelearning  bestpractices 
october 2018 by e2b
mwouts/jupytext: Jupyter notebooks as Markdown documents, Julia, Python or R scripts
Jupyter notebooks as Markdown documents, Julia, Python or R scripts - mwouts/jupytext
python  markdown  editor  collaboration  jupyter  datascience 
october 2018 by e2b
agnusmaximus/Word2Bits: Quantized word vectors that take 8x-16x less storage/memory than regular word vectors
GitHub is where people build software. More than 27 million people use GitHub to discover, fork, and contribute to over 80 million projects.
machinelearning  datascience  word2vec  nlp  language  opensource  programming  ml 
march 2018 by e2b
101 NumPy Exercises for Data Analysis (Python) - Machine Learning Plus
The goal of the numpy exercises is to serve as a reference as well as to get you to apply numpy beyond the basics. The questions are of 4 levels of difficulties with L1 being the easiest to L4 being the hardest.
python  datascience  learning  exercises  machine_learning  ml 
march 2018 by e2b
A Guide to Natural Language Processing - Federico Tomassetti - Software Architect
Natural Language Processing (NLP) offers amazing possibilities to elaborate text and extract information from it. This guide is a complete overview of NLP.
machinelearning  datascience  language 
november 2017 by e2b
Becoming a 10x Data Scientist - Algorithmia
Borrowing tips and tricks from software developers, learn how to create a more productive workflow on the journey to becoming a 10X Data Scientist.
programming  career  datascience 
september 2017 by e2b
A Practical Guide to Tree Based Learning Algorithms | Sadanand's Notes
Tree based learning algorithms are quite common in data science competitions.
These algorithms empower predictive models with high accuracy, stability and ease of
interpretation. Unlike linear models, they map non-linear relationships
quite well. Common examples of tree based models are:
decision trees,
random forest, and
boosted trees.

machine-learning  datascience  algorithms  decision-tree 
july 2017 by e2b
nteract: write your next code-driven story.
nteract is a desktop application that allows you to develop rich documents that contain prose, executable code, and images.
jupyter  programming  documentation  datascience  python  electron 
may 2017 by e2b

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