About a week ago, someone texted me over the Instagram, and asked me if I have the time to answer the questions. I was curious about the questions and wanted to see those questions. I thought maybe they won’t take time and I can easily pass them with short answers. But I gotta tell, those were solid questions and made me spend a bit more time to answer. Here are the questions and my answers.

Link: Questions about generative art and its future

#articles #spare_time
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This is a great advantage of online learning, the flexibility it provides is just awesome. You
just need a laptop or a smartphone with an internet connection and you can learn
anything.

Link: 15 Free Courses to Learn Python in 2020

#Programming
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There are over 30 beginner Python exercises just waiting to be solved. Each exercise comes with a small discussion of a topic and a link to a solution.

Link: Practice Python

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Does religion has any correlation with the number of births per women?

Link : YouTube

#Youtube
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Question:
I'm working on a project at the moment, which I'd like to eventually make public on github, but, for the moment, needs to remain private.
Github needs users to pay in order to host a private repository, which I'm unwilling to do, so just creating a private github repository is not an option for me.

Answer:
I'm dealing with the same thing. Unless that I cannot really have a private project on Github, because of unfair sanctions to some countries. I don't want to repeat the other answers, because they were straight forward, and I'm doing just the same. To add a bit information, if you don't like terminal environment and you don't want to go through every change and record them by your terminal, simply install Atom editor, install the Github plugin, in newer versions the plugin installed from the beginning and you really don't need to worry about it. When you created a folder you can initialize the git by either the Git icon or simply typing in the terminal at the exact directory:

git init

Then, when you add changes to your code or whatever, the git tracks it and you can commit your changes through the Atom editor. The only problem might be that you cannot use all of the commands that are available via terminal, but it's enough to actually work. But you can fill the gaps by using the terminal when you really need other git commands. This plugin is available on other IDEs as well. And works just fine.


Link: StackOverFlow

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In this lesson we use Git from the Unix Shell. Some previous experience with the shell is expected, but is not mandatory.
Alternatively, this course can be followed on Windows using Git Bash. All of the commands shown will work on Windows using Git Bash, with the exception of the nano command. nano is a common text editor on Linux: Windows users should use the notepad command instead, and set notepad as the core editor when configuring Git.
You will need a GitHub account for this session. Please sign up for an account if you do not already have one.

Link: Introduction-to-git-and-github

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What is interdisciplinarity? Views from students and professors in a non-major intro physics course

Ian Descamps, Thomas Moore, Benjamin Pollard

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We present an investigation into the interdisciplinary role of physics in a physics-for-non-physicists course at Pomona College. This work is guided by prior research into introductory physics for life-science (IPLS) courses, but attends to significant differences in the scope and context of this course. We interviewed enrolled students, physics professors, and professors from non-physics disciplines to explore the function of this course and the role of physics in the education of non-physics-science students. Interviews were audio recorded and transcribed, then analyzed to identify emergent themes. These themes outline the authentic physics, including content knowledge and other, broader learning objectives, that play an important and distinct role in the science education of enrolled students. Stakeholders generally align in their emphasis of interdisciplinary relevance with some divergence in the specific articulation of that idea. The differences can be understood through the stakeholders' distinct areas of expertise, with non-physics professors expressing value through relevance to their discipline and physics professors focusing on essential aspects of physics.

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عملکرد مشابه سایت سای هاب دارد.
gen.lib.rus.ec/

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Bioinformation related to COVID-19. Site developed and maintained by China National Center for Bioinformation. Collection of sequences, genome variations, publication, clinical resource data.
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Link: Bioinformatics-COVID19

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The Neuroscience Information Framework is a dynamic inventory of Web-based neuroscience resources: data, materials, and tools accessible via any computer connected to the Internet. An initiative of the NIH Blueprint for Neuroscience Research, NIF advances neuroscience research by enabling discovery and access to public research data and tools worldwide through an open source, networked environment.

Link: Neuroscience Information Framework

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Link: YouTube

#Programming #Youtube
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Link: Twitter

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MAY, R. M. (1972). Will a Large Complex System be Stable? Nature, 238(5364), 413–414. doi:10.1038/238413a0

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The goal of the NeuroElectro Project is to extract information about the electrophysiological properties (e.g. resting membrane potentials and membrane time constants) of diverse neuron types from the existing literature and place it into a centralized database.

Link: NeuroElectro

#Neuroscience

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https://www.youtube.com/watch?v=BucMrSUy0I8

#YouTube
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Denoscription:
• Projection of NeuroElectro neuron types onto space defined by the first 2 electrophysiology principal components which collectively represent ~70% of variance. Neuron types are indicated by circles and circle size is proportional to number of corresponding articles indexed in NeuroElectro database.

Interactivity:
• Click on neuron types to go to corresponding neuron page.
• Zoom in on a section of plot by dragging cursor. Zoom out by double clicking on plot.

Link: NeuroElectro

#Neuroscience
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Course Denoscription
Time series data is all around us; some examples are the weather, human behavioral patterns as consumers and members of society, and financial data. In this course, you'll learn how to calculate technical indicators from historical stock data, and how to create features and targets out of the historical stock data. You'll understand how to prepare our features for linear models, xgboost models, and neural network models. We will then use linear models, decision trees, random forests, and neural networks to predict the future price of stocks in the US markets. You will also learn how to evaluate the performance of the various models we train in order to optimize them, so our predictions have enough accuracy to make a stock trading strategy profitable.

Link: Machine Learning for Finance in Python

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