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Python Helpful Urls for Data science & Block-chain

https://towardsdatascience.com/python-for-data-science-8-concepts-you-may-have-forgotten-i-did-825966908393 https://medium.com/ub-women-data-scholars/python-vs-r-for-data-science-490e1c82ede4 https://medium.com/factory-mind/regex-tutorial-a-simple-cheatsheet-by-exa https://medium.com/neptune-insights/ultimate-cheat-sheet-to-start-coding-in-blockchain-rule-it-with-python-af355e86ba3c https://medium.com/technology-invention-and-more/how-to-build-a-simple-neural-network-in-9-lines-of-python-code-cc8f23647ca1?source=---------39--------------------- https://medium.freecodecamp.org/python-list-comprehensions-vs-generator-expressions-cef70ccb49db https://towardsdatascience.com/how-to-build-a-data-science-portfolio-5f566517c79c https://medium.com/tech-tajawal/modern-backend-developer-in-2018-6b3f7b5f8b9 https://medium.com/@msalmon00/helpful-python-code-snippets-for-data-exploration-in-pandas-b7c5aed5ecb9 https://towardsdatascience.com/object-detection-with-10-lines-of-c

Python for Data Science: 8 Concepts You May Have Forgotten

One-Line List Comprehension Writing out a for loop every time you need to define some sort of list is tedious, luckily Python has a built-in way to address this problem in just one line of code. The syntax can be a little hard to wrap your head around but once you get familiar with this technique you’ll use it fairly often. Source:  Trey Hunner See the example above and below for how you would normally go about list comprehension with a for loop vs. creating your list with in one simple line with no loops necessary. x = [1,2,3,4] out = [] for item in x: out.append(item**2) print(out) [1, 4, 9, 16] # vs. x = [1,2,3,4] out = [item**2 for item in x] print(out) [1, 4, 9, 16] Lambda Functions Ever get tired of creating function after function for limited use cases? Lambda functions to the rescue! Lambda functions are used for creating small, one-time and anonymous function objects in Python. Basically, they let you create a function,  without creating a functio

Stock Prediction in Python

Open edX installation and configuration

1  Introduction According to the [homepage],  “The Open edX platform is a free--and open source--course management system (CMS) that was originally developed by edX. The Open edX platform is used all over the world to host Massive Open Online Courses (MOOCs) as well as smaller classes and training modules.” The following content will apply to a May 2018 Ginko 2-4 installation on Ubuntu 16LTS. The Eucalyptus (2017) was described  here . See also: Open edX 2  Installation of the Bitnami stack There are  many different ways to install and run an edX server . As of March 31 2017, we managed to install a Bitnami stack as described below.  As of May 2018  some contents below are outdated. Use with care. We got it from here: https://bitnami.com/stack/edx Log onto your server machine and use something like: wget https://bitnami.com/redirect/to/193216/bitnami-edx-ginkgo.2-4-linux-x64-installer.run We also suggest to read the official  documentation of the Bitnami sta