http://www.blopig.com/blog/2016/08/processing-large-files-using-python/
Oxford Protein Informatics Group (OPIG)
Processing large files using python
In the last year or so, and with my increased focus on ribo-seq data, I have come to fully appreciate what the term #big_data means. The ribo-seq studies in their raw forms can easily reach into hundreds of GBs, which means that processing them in both a timely and efficient manner requires some thought. In this blog post, and hopefully those following, I want to detail some of the methods I have come up (read: pieced together from multiple stack exchange posts), that help me take on data of this magnitude. Specifically I will be detailing methods for #python and R, though some of the methods are transferrable to other languages.
https://django-ai.readthedocs.io/en/latest/readme.html
#Artificial_Intelligence for #Django
django-ai is a collection of apps for integrating statistical models into your Django project so you can implement #Machine_Learning conveniently.
https://hackernoon.com/absolute-fundamentals-of-machine-learning-dca5deee78df?gi=2c99287cb9f5
#machine_learning , what a buzzword. I’m sure you all want to understand machine learning, and that’s what I’m going to teach in this article.
I found that learning the theroetical side alongside the programming side makes it easier to learn both, so this article features both easy to understand mathematics and the algorithms implemented in Python. Also, technology becomes outdated — fast. The code used in this tutorial will likely be meaningless in 5 years time. So for that reason, I’ve decided to also teach the mathematical side to Machine Learning that will not die out in a few years.
https://www.udemy.com/machinelearning/learn/v4/content
#machine_learning A-Z™: Hands-On #Python & R In #Data_Science
https://machinelearningmastery.com/setup-python-environment-machine-learning-deep-learning-anaconda/
It can be difficult to install a #Python#machine_learning environment on some platforms.
Python itself must be installed first and then there are many packages to install, and it can be confusing for beginners.
In this tutorial, you will discover how to set up a Python machine learning development environment using #Anaconda.
https://www.analyticsvidhya.com/blog/2016/08/deep-learning-path/?utm_content=bufferd56c5&utm_medium=social&utm_source=linkedin.com&utm_campaign=buffer
#Deep_Learning, a prominent topic in #Artificial_Intelligence domain, has been in the spotlight for quite some time now. It is especially known for its breakthroughs in fields like Computer Vision and Game playing (Alpha GO), surpassing human ability. Since the last survey, there has been a drastic increase in the trends. (click here to check out the survey)
Here is what Google trends shows us:
https://goo.gl/ucbkhT
#Data_Science for #Big_Data with #Anaconda Enterprise
Getting Python and R’s most popular data science libraries to work on a computational cluster can be a major challenge. And in a Big Data world, surmounting this challenge is key to leveraging data science within your organization to make smart, data-driven decisions.
https://impact.apartmentocean.com/20-buzzwords-know-artificial-intelligence/
20 Buzzwords you have to know in #Artificial_Intelligence
1. #AI (Artificial Intelligence)
2. #Cloud_Computing
3. #Big_Data
4. Algorithm
5. #Python
6. #Data_Warehouse
7. #Machine_Learning
8. #Deep_Learning
9. #Artificial_Neural_Network
10. #Chatbot
11. #Data_Mining
12. Predictive Analytics
13. #OCR (#Optical_Character_Reader)
14. #AlphaGo and #Deepmind
15. #AWS (#Amazon_Web_Services)
16. #IBM_Watson
17. #Yottabyte
18. #NLP (#Natural_Language_Processing)
19. #IOT (#Internet_of_Things)
20. #Smart_City
http://www.aparat.com/v/0scM5
Irene Chen A Beginner's Guide to Deep Learning.
What is #Deep_Learning ? It has recently exploded in popularity as a complex and incredibly powerful tool. This talk will present the basic concepts underlying deep learning in understandable pieces for complete beginners to #machine_learning.
http://www.aparat.com/v/Corus
Advanced users #Deep_Learning, anyone who has followed #machine_learning over the past years has heard it. In this talk I will go past the hype and show what deep learning actually means and how one goes about solving complex machine learning task with a minimum amount of code, with the help of theano, an amazing python library for deep learning.