adarsh0806
Environmentalist. Machine Learning Engineer. 'Computer Science is no more about computers than astronomy is about telescopes.' EW Dijkstra
San Francisco
adarsh0806's Stars
vinta/awesome-python
An opinionated list of awesome Python frameworks, libraries, software and resources.
josephmisiti/awesome-machine-learning
A curated list of awesome Machine Learning frameworks, libraries and software.
awesomedata/awesome-public-datasets
A topic-centric list of HQ open datasets.
donnemartin/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.
academic/awesome-datascience
:memo: An awesome Data Science repository to learn and apply for real world problems.
ChristosChristofidis/awesome-deep-learning
A curated list of awesome Deep Learning tutorials, projects and communities.
scala/scala
Scala 2 compiler and standard library. Scala 2 bugs at https://github.com/scala/bug; Scala 3 at https://github.com/scala/scala3
mwaskom/seaborn
Statistical data visualization in Python
dive-into-machine-learning/dive-into-machine-learning
Free ways to dive into machine learning with Python and Jupyter Notebook. Notebooks, courses, and other links. (First posted in 2016.)
rushter/data-science-blogs
A curated list of data science blogs
rhiever/Data-Analysis-and-Machine-Learning-Projects
Repository of teaching materials, code, and data for my data analysis and machine learning projects.
kjw0612/awesome-rnn
Recurrent Neural Network - A curated list of resources dedicated to RNN
rasbt/pattern_classification
A collection of tutorials and examples for solving and understanding machine learning and pattern classification tasks
Quartz/bad-data-guide
An exhaustive reference to problems seen in real-world data along with suggestions on how to resolve them.
hal9ai/awesome-dataviz
:chart_with_upwards_trend: A curated list of awesome data visualization libraries and resources.
bqplot/bqplot
Plotting library for IPython/Jupyter notebooks
simple-statistics/simple-statistics
simple statistics for node & browser javascript
scikit-learn-contrib/sklearn-pandas
Pandas integration with sklearn
szilard/benchm-ml
A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).
ogrisel/parallel_ml_tutorial
Tutorial on scikit-learn and IPython for parallel machine learning
DrSkippy/Data-Science-45min-Intros
Ipython notebook presentations for getting starting with basic programming, statistics and machine learning techniques
summanlp/textrank
TextRank implementation for Python 3.
iamaziz/PyDataset
Instant access to many datasets in Python.
dataproofer/Dataproofer
A proofreader for your data
derek73/python-nameparser
A simple Python module for parsing human names into their individual components
NathanEpstein/Dora
Tools for exploratory data analysis in Python
brandomr/document_cluster
A guide to document clustering in Python
stitchfix/d3-jupyter-tutorial
mikemull/Notebooks
Ipython notebooks on various topics
cchi/viral-markov