This document discusses tools for data scientists. It begins with an introduction of the presenter and agenda. It then covers topics like data science, the data science process, notebooks/IDEs, methods and algorithms, software, deep learning tools, programming languages, cloud services, and computing power. Specific tools mentioned include Jupyter Notebook, RStudio, TensorFlow, Python, and cloud services from Amazon, Azure, and Google. The document concludes by introducing FlyElephant as a solution for high performance computing, data science engineering, and more.

1. Tools for
Data Scientists
Dmitry Spodarets

2. Who am I
Dmitry Spodarets
• CEO and Founder at FlyElephant
• Lecturer at Odessa Polytechnic
University
• Organizer of technical
conferences about AI, BigData,
HPC, JS, FOSS …

3. Agenda
• Data Science
• Data Scientist vs Data Engineer
• Data science process
• Notebook / IDE
• Methods & Algorithms
• Software
• Deep Learning Tools
• Programming Languages
• Cloud Services
• Computing power
• FlyElephant

4. Big Data

5. Data Growth

6. Dataset volumes

7. Data Science

8. Data Scientist

10. Data Scientist vs Data Engineer

11. Data science process

12. Notebook / IDE

13. Jupyter Notebook

14. RStudio

15. Methods & Algorithms
http://www.kdnuggets.com/2016/09/poll-algorithms-used-data-scientists.html

16. Software

17. Software
New (in this poll) tools that received at least 1% share votes in
2016 were:
• Anaconda, 16%
• Microsoft other ML/Data Science tools, 1.6%
• SAP HANA, 1.2%
• XLMiner, 1.2%

18. Software
• Tools with the highest growth (among tools with at least 15
users in 2015) were

19. Deep Learning Tools
• Tensorflow, 6.8%
• Theano ecosystem (including Pylearn2), 5.1%
• Caffe, 2.3%
• MATLAB Deep Learning Toolbox, 2.0%
• Deeplearning4j, 1.7%
• Torch, 1.0%
• Microsoft CNTK, 0.9%
• Cuda-convnet, 0.8%
• mxnet, 0.6%
• Convnet.js, 0.3%
• darch, 0.1%
• Nervana, 0.1%
• Veles, 0.1%
• Other Deep Learning Tools, 3.7%

20. Programming Languages
• Python, 45.8% share (was 30.3%), 51% increase
• Java, 16.8% share (was 14.1%), 19% increase
• Unix shell/awk/gawk 10.4% share (was 8.0%), 30% increase
• C/C++, 7.3% share (was 9.4%), 23% decrease
• Other programming/data languages, 6.8% share (was 5.1%),
34.1% increase
• Scala, 6.2% share (was 3.5%), 79% increase
• Perl, 2.3% share (was 2.9%), 19% decrease
• Julia, 1.1% share (was 1.1%), 1.6% decrease
• F#, 0.4% share (was 0.7%), 41.8% decrease
• Clojure, 0.4% share (was 0.5%), 19.4% decrease
• Lisp, 0.2% share (was 0.4%), 33.3% decrease

21. Cloud Services
Amazon Machine Learning
Azure Machine Learning
Google Machine Learning

22. Computing power

23. Computing power
NVIDIA DGX-1 Deep Learning Supercomputer
170/3 TFLOPS (GPU FP16 / CPU FP32)
intel xeon phi processor
nvidia tesla p100
~5 TeraFLOPS
~3 TeraFLOPS

25. Your Home for High Performance Computing
Compute ● Collaborate ● Manage

26. Solutions for
Data Science Engineering
Simulation
Rendering Academia

27. Cloud computing

28. Tools

29. Computing on a HPC cluster

30. Support of Docker

31. WebTools: Notebooks

32. Storage

33. WebTools: VNC Desktop

34. Community of experts

35. Projects

36. Billing

38. www.flyelephant.net

39. slack.flyelephant.net

40. Dmitry Spodarets
d.spodarets@flyelephant.net
www.flyelephant.net