Logos converted

Author: Krzysztof Joachimiak

README.md

@@ -24,10 +24,6 @@
 
 [gpu]: https://raw.githubusercontent.com/krzjoa/awesome-python-datascience/master/img/gpu.png 'GPU accelerated'
 
-[sp]: https://raw.githubusercontent.com/krzjoa/awesome-python-datascience/master/img/spark.png 'Apache Spark based'
-
-[amd]: https://raw.githubusercontent.com/krzjoa/awesome-python-datascience/master/img/amd.png 'possible to run on AMD'
-
 ## Contents
 * [Machine Learning](#ml)
 * [Deep Learning](#dl)
@@ -61,7 +57,7 @@
 * [xLearn](https://github.com/aksnzhy/xlearn) - High Performance, Easy-to-use, and Scalable Machine Learning Package.
 * [cuML](https://github.com/rapidsai/cuml) - RAPIDS Machine Learning Library. <img height="20" src="img/sklearn_big.png" alt="sklearn"> ![alt text][gpu]
 * [modAL](https://github.com/cosmic-cortex/modAL) - Modular active learning framework for Python3. <img height="20" src="img/sklearn_big.png" alt="sklearn">
-* [Sparkit-learn](https://github.com/lensacom/sparkit-learn) - PySpark + scikit-learn = Sparkit-learn. <img height="20" src="img/sklearn_big.png" alt="sklearn"> ![alt text][sp]
+* [Sparkit-learn](https://github.com/lensacom/sparkit-learn) - PySpark + scikit-learn = Sparkit-learn. <img height="20" src="img/sklearn_big.png" alt="sklearn"> <img height="20" src="img/spark_big.png" alt="Apache Spark based">
 * [mlpack](https://github.com/mlpack/mlpack) - A scalable C++ machine learning library (Python bindings).
 * [dlib](https://github.com/davisking/dlib) - Toolkit for making real world machine learning and data analysis applications in C++ (Python bindings).
 * [MLxtend](https://github.com/rasbt/mlxtend) - Extension and helper modules for Python's data analysis and machine learning libraries. <img height="20" src="img/sklearn_big.png" alt="sklearn">
@@ -155,9 +151,9 @@
 * [TensorForce](https://github.com/reinforceio/tensorforce) - A TensorFlow library for applied reinforcement learning. <img height="20" src="img/tf_big2.png" alt="sklearn">
 * [tensorpack](https://github.com/ppwwyyxx/tensorpack) - A Neural Net Training Interface on TensorFlow <img height="20" src="img/tf_big2.png" alt="sklearn">
 * [Polyaxon](https://github.com/polyaxon/polyaxon) - A platform that helps you build, manage and monitor deep learning models. <img height="20" src="img/tf_big2.png" alt="sklearn">
-* [NeuPy](https://github.com/itdxer/neupy) - NeuPy is a Python library for Artificial Neural Networks and Deep Learning (previously: <img height="20" src="img/theano_big.png" alt="sklearn">). <img height="20" src="img/tf_big2.png" alt="sklearn">
+* [NeuPy](https://github.com/itdxer/neupy) - NeuPy is a Python library for Artificial Neural Networks and Deep Learning (previously: <img height="20" src="img/theano_big.png" alt="Theano compatible">). <img height="20" src="img/tf_big2.png" alt="sklearn">
 * [tfdeploy](https://github.com/riga/tfdeploy) - Deploy tensorflow graphs for fast evaluation and export to tensorflow-less environments running numpy. <img height="20" src="img/tf_big2.png" alt="sklearn">
-* [tensorflow-upstream](https://github.com/ROCmSoftwarePlatform/tensorflow-upstream) - TensorFlow ROCm port. <img height="20" src="img/tf_big2.png" alt="sklearn"> ![alt text][amd]
+* [tensorflow-upstream](https://github.com/ROCmSoftwarePlatform/tensorflow-upstream) - TensorFlow ROCm port. <img height="20" src="img/tf_big2.png" alt="sklearn"> <img height="20" src="img/amd_big.png" alt="Possible to run on AMD GPU">
 * [TensorFlow Fold](https://github.com/tensorflow/fold) - Deep learning with dynamic computation graphs in TensorFlow. <img height="20" src="img/tf_big2.png" alt="sklearn">
 * [tensorlm](https://github.com/batzner/tensorlm) - Wrapper library for text generation / language models at char and word level with RNN. <img height="20" src="img/tf_big2.png" alt="sklearn">
 * [TensorLight](https://github.com/bsautermeister/tensorlight) - A high-level framework for TensorFlow. <img height="20" src="img/tf_big2.png" alt="sklearn">
@@ -182,7 +178,7 @@
 * [gluon-cv](https://github.com/dmlc/gluon-cv) - Provides implementations of the state-of-the-art deep learning models in computer vision. ![alt text][mx]
 * [gluon-nlp](https://github.com/dmlc/gluon-nlp) - NLP made easy. ![alt text][mx]
 * [Xfer](https://github.com/amzn/xfer) - Transfer Learning library for Deep Neural Networks. ![alt text][mx]
-* [MXNet](https://github.com/ROCmSoftwarePlatform/mxnet) - HIP Port of MXNet. ![alt text][mx] ![alt text][amd]
+* [MXNet](https://github.com/ROCmSoftwarePlatform/mxnet) - HIP Port of MXNet. ![alt text][mx] <img height="20" src="img/amd_big.png" alt="Possible to run on AMD GPU">
 
 <!--a name="dl-cntk"></a-->
 <a name="dl-chainer"></a>
@@ -195,13 +191,13 @@
 <a name="dl-theano"></a>
 ### Theano
 **WARNING: Theano development has been stopped**
-* [Theano](https://github.com/Theano/Theano) - A Python library that allows you to define, optimize, and evaluate mathematical expressions.<img height="20" src="img/theano_big.png" alt="sklearn">
-* [Lasagne](https://github.com/Lasagne/Lasagne) - Lightweight library to build and train neural networks in Theano. <img height="20" src="img/theano_big.png" alt="sklearn">
-* [nolearn](https://github.com/dnouri/nolearn) - A scikit-learn compatible neural network library (mainly for Lasagne). <img height="20" src="img/theano_big.png" alt="sklearn"> <img height="20" src="img/sklearn_big.png" alt="sklearn">
-* [Blocks](https://github.com/mila-udem/blocks) - A Theano framework for building and training neural networks. <img height="20" src="img/theano_big.png" alt="sklearn">
-* [scikit-neuralnetwork](https://github.com/aigamedev/scikit-neuralnetwork) - Deep neural networks without the learning cliff. <img height="20" src="img/sklearn_big.png" alt="sklearn"> <img height="20" src="img/theano_big.png" alt="sklearn">
-* [platoon](https://github.com/mila-udem/platoon) - Multi-GPU mini-framework for Theano. <img height="20" src="img/theano_big.png" alt="sklearn">
-* [Theano-MPI](https://github.com/uoguelph-mlrg/Theano-MPI) - MPI Parallel framework for training deep learning models built in Theano. <img height="20" src="img/theano_big.png" alt="sklearn">
+* [Theano](https://github.com/Theano/Theano) - A Python library that allows you to define, optimize, and evaluate mathematical expressions.<img height="20" src="img/theano_big.png" alt="Theano compatible">
+* [Lasagne](https://github.com/Lasagne/Lasagne) - Lightweight library to build and train neural networks in Theano. <img height="20" src="img/theano_big.png" alt="Theano compatible">
+* [nolearn](https://github.com/dnouri/nolearn) - A scikit-learn compatible neural network library (mainly for Lasagne). <img height="20" src="img/theano_big.png" alt="Theano compatible"> <img height="20" src="img/sklearn_big.png" alt="sklearn">
+* [Blocks](https://github.com/mila-udem/blocks) - A Theano framework for building and training neural networks. <img height="20" src="img/theano_big.png" alt="Theano compatible">
+* [scikit-neuralnetwork](https://github.com/aigamedev/scikit-neuralnetwork) - Deep neural networks without the learning cliff. <img height="20" src="img/sklearn_big.png" alt="sklearn"> <img height="20" src="img/theano_big.png" alt="Theano compatible">
+* [platoon](https://github.com/mila-udem/platoon) - Multi-GPU mini-framework for Theano. <img height="20" src="img/theano_big.png" alt="Theano compatible">
+* [Theano-MPI](https://github.com/uoguelph-mlrg/Theano-MPI) - MPI Parallel framework for training deep learning models built in Theano. <img height="20" src="img/theano_big.png" alt="Theano compatible">
 
 <a name="dl-others"></a>
 ### Others
@@ -213,7 +209,7 @@
 * [nnabla](https://github.com/sony/nnabla) - Neural Network Libraries by Sony.
 * [Caffe](https://github.com/BVLC/caffe) - A fast open framework for deep learning.
 * [Caffe2](https://github.com/pytorch/pytorch/tree/master/caffe2) - A lightweight, modular, and scalable deep learning framework (now a part of PyTorch).
-* [hipCaffe](https://github.com/ROCmSoftwarePlatform/hipCaffe) - The HIP port of Caffe. ![alt text][amd]
+* [hipCaffe](https://github.com/ROCmSoftwarePlatform/hipCaffe) - The HIP port of Caffe. <img height="20" src="img/amd_big.png" alt="Possible to run on AMD GPU">
 
 <a name="data-man"></a>
 ## Data Manipulation
@@ -226,7 +222,7 @@
 * [pandasql](https://github.com/yhat/pandasql) - Allows you to query pandas DataFrames using SQL syntax. <img height="20" src="img/pandas_big.png" alt="pandas compatible">
 * [pandas-gbq](https://github.com/pydata/pandas-gbq) - pandas Google Big Query. <img height="20" src="img/pandas_big.png" alt="pandas compatible">
 * [xpandas](https://github.com/alan-turing-institute/xpandas) - Universal 1d/2d data containers with Transformers .functionality for data analysis by [The Alan Turing Institute](https://www.turing.ac.uk/).
-* [pysparkling](https://github.com/svenkreiss/pysparkling) - A pure Python implementation of Apache Spark's RDD and DStream interfaces. ![alt text][sp]
+* [pysparkling](https://github.com/svenkreiss/pysparkling) - A pure Python implementation of Apache Spark's RDD and DStream interfaces. <img height="20" src="img/spark_big.png" alt="Apache Spark based">
 * [Arctic](https://github.com/manahl/arctic) - High performance datastore for time series and tick data.
 * [datatable](https://github.com/h2oai/datatable) - Data.table for Python. ![alt text][r]
 * [koalas](https://github.com/databricks/koalas) - pandas API on Apache Spark. <img height="20" src="img/pandas_big.png" alt="pandas compatible">
@@ -311,7 +307,7 @@
 <a name="dist"></a>
 ## Distributed Computing
 * [Horovod](https://github.com/uber/horovod) - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. <img height="20" src="img/tf_big2.png" alt="sklearn">
-* [PySpark](https://spark.apache.org/docs/0.9.0/python-programming-guide.html) - Exposes the Spark programming model to Python. ![alt text][sp]
+* [PySpark](https://spark.apache.org/docs/0.9.0/python-programming-guide.html) - Exposes the Spark programming model to Python. <img height="20" src="img/spark_big.png" alt="Apache Spark based">
 * [Veles](https://github.com/Samsung/veles) - Distributed machine learning platform.
 * [Jubatus](https://github.com/jubatus/jubatus) - Framework and Library for Distributed Online Machine Learning.
 * [DMTK](https://github.com/Microsoft/DMTK) - Microsoft Distributed Machine Learning Toolkit.
@@ -325,13 +321,13 @@
 * [pyro](https://github.com/uber/pyro) - A flexible, scalable deep probabilistic programming library built on PyTorch. <img height="20" src="img/pytorch_big2.png" alt="PyTorch based/compatible">
 * [ZhuSuan](http://zhusuan.readthedocs.io/en/latest/) - Bayesian Deep Learning. <img height="20" src="img/tf_big2.png" alt="sklearn">
 * [PyMC](https://github.com/pymc-devs/pymc) - Bayesian Stochastic Modelling in Python.
-* [PyMC3](http://docs.pymc.io/) - Python package for Bayesian statistical modeling and Probabilistic Machine Learning. <img height="20" src="img/theano_big.png" alt="sklearn">
+* [PyMC3](http://docs.pymc.io/) - Python package for Bayesian statistical modeling and Probabilistic Machine Learning. <img height="20" src="img/theano_big.png" alt="Theano compatible">
 * [sampled](https://github.com/ColCarroll/sampled) - Decorator for reusable models in PyMC3.
 * [Edward](http://edwardlib.org/) - A library for probabilistic modeling, inference, and criticism. <img height="20" src="img/tf_big2.png" alt="sklearn">
 * [InferPy](https://github.com/PGM-Lab/InferPy) - Deep Probabilistic Modelling Made Easy. <img height="20" src="img/tf_big2.png" alt="sklearn">
 * [GPflow](http://gpflow.readthedocs.io/en/latest/?badge=latest) - Gaussian processes in TensorFlow. <img height="20" src="img/tf_big2.png" alt="sklearn">
 * [PyStan](https://github.com/stan-dev/pystan) - Bayesian inference using the No-U-Turn sampler (Python interface).
-* [gelato](https://github.com/ferrine/gelato) - Bayesian dessert for Lasagne. <img height="20" src="img/theano_big.png" alt="sklearn">
+* [gelato](https://github.com/ferrine/gelato) - Bayesian dessert for Lasagne. <img height="20" src="img/theano_big.png" alt="Theano compatible">
 * [sklearn-bayes](https://github.com/AmazaspShumik/sklearn-bayes) - Python package for Bayesian Machine Learning with scikit-learn API. <img height="20" src="img/sklearn_big.png" alt="sklearn">
 * [skggm](https://github.com/skggm/skggm) - Estimation of general graphical models. <img height="20" src="img/sklearn_big.png" alt="sklearn">
 * [pgmpy](https://github.com/pgmpy/pgmpy) - A python library for working with Probabilistic Graphical Models.