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Aug 27, 2020
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statistical-learning
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A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.
machine-learning
reinforcement-learning
ai
deep-learning
neural-network
statistical-learning
artificial-intelligence
unsupervised-learning
intelligent-systems
machine-intelligence
intelligent-machines
An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code
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May 7, 2020 - Jupyter Notebook
A collection of research papers on decision, classification and regression trees with implementations.
classifier
machine-learning
random-forest
statistical-learning
xgboost
lightgbm
gradient-boosting-machine
ensemble-learning
cart
decision-tree
tree-ensemble
decision-tree-classifier
gradient-boosting
classification-trees
decision-tree-learning
decision-tree-model
classification-model
catboost
regression-tree
machine-learning-research
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Aug 2, 2020 - Python
Highly cited and useful papers related to machine learning, deep learning, AI, game theory, reinforcement learning
data-science
machine-learning
data-mining
statistics
reinforcement-learning
deep-learning
neural-network
hardware
paper
machine-learning-algorithms
statistical-learning
artificial-intelligence
game-theory
pattern-recognition
literature
silicon
learning-theory
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Aug 6, 2020
JasonShin
commented
Apr 8, 2019
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I'm submitting a ...
[/] enhancement -
Summary
As a result of upgrading the Tensorflow version to 0.15.1, we should refactor all thedataSycnwitharraySync. This will greatly improve the overall readability of the code.
Jupyter Notebooks for Springer book "Python for Probability, Statistics, and Machine Learning"
python
machine-learning
statistics
books
book
probability
jupyter-notebook
statistical-learning
statistical-analysis
statistical-tests
probability-theory
statistics-course
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Nov 6, 2019 - Jupyter Notebook
Teaching Materials for Dr. Waleed A. Yousef
computer-science
data-science
machine-learning
statistics
programming
optimization
linear-algebra
probability
mathematics
statistical-learning
image-processing
data-visualization
data-structures
discrete-mathematics
pattern-recognition
statistical-models
digital-design
logic-design
analysis-of-algorithms
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Aug 27, 2020 - Mathematica
A series of Python Jupyter notebooks that help you better understand "The Elements of Statistical Learning" book
python
data-science
machine-learning
tensorflow
sklearn
statistical-learning
tutorials
data-analysis
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Jan 15, 2020 - Jupyter Notebook
Jupyter notebooks for summarizing and reproducing the textbook "The Elements of Statistical Learning" 2/E by Hastie, Tibshirani, and Friedman
machine-learning
neural-network
statistical-learning
python3
pytorch
scipy
matplotlib
textbook
jupyter-notebooks
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May 5, 2018 - Jupyter Notebook
My notes and codes (jupyter notebooks) for the "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani and Jerome Friedman
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Jul 6, 2020 - Jupyter Notebook
Lecture Slides and R Sessions for Trevor Hastie and Rob Tibshinari's "Statistical Learning" Stanford course
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Jan 2, 2018 - R
统计学习方法训练营课程作业及答案,视频笔记在线阅读地址:https://relph1119.github.io/statistical-learning-method-camp
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Aug 6, 2020 - Jupyter Notebook
TAPAS - Translational Algorithms for Psychiatry-Advancing Science
statistical-learning
neuroscience
eeg
computational
fmri
bayesian-inference
behavioral
hierarchical-models
psychiatry
psychosomatics
neurology
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Sep 9, 2020 - MATLAB
An Introduction to Statistical Learning with Applications in PYTHON
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Feb 12, 2019 - Jupyter Notebook
machine-learning
natural-language-processing
computer-vision
deep-learning
statistical-learning
video-camera
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Sep 29, 2019
Generalized Linear Models in Sklearn Style
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Apr 22, 2020 - Python
Advanced Normalization Tools in R
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Sep 17, 2020 - R
Solutions to labs and excercises from An Introduction to Statistical Learning, as Jupyter Notebooks.
bootstrap
machine-learning
random-forest
linear-regression
statistical-learning
supervised-learning
pca
logistic-regression
boosting-algorithms
lda
islr
bagging
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Jul 12, 2019 - Jupyter Notebook
Introduction to Statistical Learning with R을 Python으로
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Nov 25, 2017 - Jupyter Notebook
A list of classic books make better you understand not only how it works, but why it works.
machine-learning
reinforcement-learning
computer-vision
deep-learning
linear-algebra
statistical-learning
inference
stanford-university
high-performance-computing
bayesian-inference
computer-architecture
probabilistic-graphical-models
hao
5th
robert-tibshirani
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Aug 15, 2020
D-Lab's Machine Learning Working Group at UC Berkeley, with supervised & unsupervised learning tutorials in R and Python
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Mar 10, 2019 - HTML
李航《统计学习方法》笔记和 Python 实现(不基于任何代数运算库)。
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Nov 4, 2018 - Python
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Apr 16, 2020 - Shell
Fixed Income Analytics, Portfolio Construction Analytics, Transaction Cost Analytics, Counter Party Analytics, Asset Backed Analytics
java
statistical-learning
bond
portfolio-optimization
fx
market-risk
loans
interest-rates
asset-allocation
treasury
fixed-income
transaction-cost-analytics
cva-dva-fva-kva-xva
asset-backed
credit-risk
counterparty-risk
corporates
municipals
emerging-market
inflation-linked
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Sep 13, 2020 - HTML
SuperLearner guide: fitting models, ensembling, prediction, hyperparameters, parallelization, timing, feature selection, etc.
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Apr 17, 2019 - HTML
Statistical Models with Regularization in Pure Julia
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Apr 22, 2020 - Julia
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I'm sorry if I missed this functionality, but
CLIversion hasn't it for sure (I saw the related code only ingenerate_code_examples.py). I guess it will be very useful to eliminate copy-paste phase, especially for large models.Of course, piping is a solution, but not for development in Jupyter Notebook, for example.