Get the scoop on the technology we worked on around inauguration day.

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Welcome back

Welcome back everyone, and thank you for taking the time to read the latest installment of the chifi chronicle. The chifi chronicle is an all-in-one newsletter for things happening in all of the chifi communities, product updates, open-source updates, and more.

This Week At Chifi Media

Introducing Chifi Source

https://medium.com/chifi-media/introducing-chifi-source-a-platform-for-research-and-creation-50e08a4fb970

Chifi Source Community Updates

https://medium.com/chifi-media/chifi-source-community-update-01-15-2021-43a5becf6b95

https://medium.com/chifi-media/chifi-source-community-update-1e3c2e412d06

This week’s source

There are so many exciting recent projects that are now being open-sourced at Chifi and I am excited for all of you to check out. …


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Hey everybody!

I am back and excited to update the Chifi community on what has been worked on over the past few days in the Chifi Source organization. These include additions to old packages, some updates on products you might be tracking, updating our websites, and finally some new faces that you might not have actually expected to see!

OddFrames


I got tired of the way DataFrames acted, so I made my own.

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Introduction

Something that has only been reiterated to me in my Data Science experience is the actual value of 1-dimensional data in scientific computing. The great thing about taking a 1-dimensional approach to data in many instances is that many machine-learning tasks involve shaping 1-dimensional data, and many tools don’t like to take data in multiple dimensions.

That being said, dimensional is something I find to be very flexible. Take a 1-dimensional array and put another 1-dimensional array below it, and instantly we have dimensions of (2, x). …


10 more of my favorite books I use to dominate machine-learning part of Data Science in Python.

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Introduction

Let’s face the facts:

Data Science Is Hard

Learning Data Science in the first place is incredibly taxing, and could certainly be difficult. This is especially true for those coming into the language with little-to-no experience or prior knowledge. Data Science is particularly difficult because it requires a certain subset of skills that can be found in many professional fields. While often these skills are separated and might only be used by one discipline or the other, Data Scientists have to combine all of these skills into one.

A Data Scientist must become proficient in not only programming, but also statistics and business. Statistics and business alone have enough depth to them to make you rip your hair out, not to mention the whole programming thing. On top of the ability to do basic programming is the ability to write algorithms. While Data Scientists utilize the rules of general applied science and try to prove hypothesizes, Data Scientists also need to apply those statistics in an automated fashion to provide real-time results to solve problems. This is a topic that most Data Scientists will be familiar with, it is called machine-learning. …


A quick introduction to Julia with information on resources and packages commonly used for ML in the language.

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Introduction

Since its inception, the scientific community has been a particularly hard beast to appeal to with programming languages. This is of course in reference to scientists who are scientists first, and computer scientists second. A new aspiring Data Scientist who has never read an ounce of code in their life would certainly have a lot of difficulty learning a lower-level language like C++. Furthermore, the paradigm of this language might restrict the ability of the scientist by requiring entire type structures in order to do some basic tests that declarative programming would have definitely been optimal for.

That being said, while declarative syntax is most certainly optimal for scientific computing, something it is not optimal for is speed. Speed seems to be Julia’s resounding benefit, although there are far more features in the language that make it an even more valuable asset for Data Science. Scientists need both the fast numerical calculation and state management of a more iterative language while also needing the methodology and ease-of-use of declarative programming. …


What skills is the market looking for, and what should you pick up for the new year?

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Introduction

With a field as radically changing with constant progression like data science, it is easy to see why sometimes the most in-demand tools for any given moment in time might be quite difficult to obtain. A key portion of being a data scientist is researching and becoming familiar with modern technologies that are at your disposal at any given moment. You never know when you might need a tool, function, or module that you have never used before, and thus need to first learn how to use it. That’s why most of us read Towards Data Science!

The biggest handicap to the data science discipline has been its enormous growth spurt over the past few years. In recent years, data science has turned from a relatively lesser-known field to the hottest job of the next decade. That being said, the ecosystem is also moving this fast. This means that it is very common and hard not to get out-paced if you don’t remain on your feet. …


An update on the open-source technologies being developed at chifi source.

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we missed a day, but it’s okay.

Introduction

Although we might be a hair late on this overview, today’s update is very exciting and I think some of the initialized technology is pretty cool! While there are plenty of really cool concepts being built out in this regard over at chifi source, we are going to be looking at a new inception today that is going to mark the first launch of an official chifi application. With that in mind, today’s update is going to primarily be focused on the development of the application.

There are a lot of things that can effect performance, such as mood, and stress. A common theme between a bad mood and being stressed is not having adequate sleep. Sleeping is an important part of the process of daily lives and all sorts of chemical reactions take place in your brain during sleep. These chemicals can connect to growth, brain development, and bad sleep can play a significant role in ones personal life. …


A detailed overview of how things went this week at Chifi!

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The Chronicle — An Introduction

Welcome to the Chifi Chronicle, a weekly newsletter from the same people that bring you both Chifi Media and Chifi Source. The intention of this newsletter is to keep interested and involved partners, consumers, and general audiences up-to-date on what we have been working on. There is a lot of really cool stuff going on at Chifi from application, web, and game development to scientific computing in the name of software freedom — so this is certainly a newsletter worth subscribing to!

Featured Chifi Media Content

Introducing Chifi Source …

https://medium.com/chifi-media/introducing-chifi-source-a-platform-for-research-and-creation-50e08a4fb970

Should we be using Lisp for Data Science?

https://medium.com/chifi-media/should-we-be-using-lisp-for-data-science-13136306d273

Our first Chifi Source community update!

https://medium.com/chifi-media/chifi-source-community-update-01-15-2021-43a5becf6b95

Thank you for reading!


A bi-daily update on the software currently being developed by the Chifi Source community!

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Introduction

This is the Chifi Source, bi-daily update — which I will now be composing every two days in light of the recent (and exciting!) work being done on open-source scientific computing by Chifi Source. There are some exciting projects and some awesome concepts that I am extremely excited to present in todays update. Today is 01/15/2021, and as of right now the Chifi Source organization is now the owner of four fine repositories!

If Chifi Source is an entirely new concept to you, don’t worry! …


Make your algebra perfect with these 30 great NumPy tricks

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Introduction

Unless you’re either brand new to Data Science, or somehow have a dial-up connection and live in a terminal with out-dated software, it is likely you have heard of NumPy. NumPy is one of the quintessential Data Science packages in the Python programming language. NumPy in a nutshell is a library that can be used to perform linear algebra and arithmetic with. However, as users of the software will certainly be able to iterate, it does a lot more than that, as well!

NumPy is a vast library that has been built and iterated upon. A great thing about this is that all of the Pythonic Data Science ecosystem, or even mathematical ecosystem already uses NumPy for linear algebra. Great examples of this are packages like SkLearn or even more-so; Pandas. For many Scientific programmers, the spectacular power of NumPy for Python might have even moved them into the language. …

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