Consequences of mistaking models for software

Twelve traps to avoid when building and deploying models

In Part 1 of this series on data scientists are from Mars and software engineers are from Venus we examined the five key dimensions of difference between software and models. The natural follow on question to ask is — So What? Does it really matter if models are conflated with software and data scientists are treated as software engineers? After all for a large cross-section of the population, and more importantly the business world, the similarities between them are far more visible than their differences. In fact, Andrej Karpathy refers to this new way of solving problems using models as Software 2.0. If they are really the next iteration of software are these differences really consequential. Read More

#data-science, #devops

Data Scientists are from Mars and Software Developers are from Venus (Part 1)

Mars and Venus are very different planets. Mars’s atmosphere is very thin and it can get very cold; while Venus’s atmosphere is very thick and it can get very hot — hot enough to melt lead!.

…Software Engineers and Data Scientists come from two different worlds — one from Venus and the other from Mars. They have different backgrounds mindsets, and deal with different sets of issues. They have a number of things in common too. In this and subsequent blogs we will look at the key differences (and similarities) between them and why those differences exist and what kind of bridge we need to create between them. In this blog, we explore the fundamental differences between software and models. Read More

#data-science, #devops

5 Concrete Real-World Projects to Build Up Your Data Science Portfolio

Do you want to enter the data science world? Congratulations! That’s (still) the right choice.

The market currently gets tougher. So, you must be mentally prepared for a long hiring journey and many rejections. I assume that you have already read that a data science portfolio is crucial and how to build it up. Most of the time, you will do data crunching and wrangling and not applying fancy models.

One question that I am asked on and on is about concrete data sources for cool data and project opportunities to build such a portfolio. Read More

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How Do Data Science Machine Learning And Artificial Intelligence Overlap

In conjunction with data science and digital transformation, you have probably heard the terms of artificial intelligence, machine learning, and deep learning is used. You might wonder what the relationship between those topics is. How do companies in industries range from biopharma to chemicals to food & beverage that incorporate AI, machine learning, and data science to enhance their processes? AI and machine learning allow applications such as virtual digital assistants, facial recognition, and self-driving cars, as well as improvements in healthcare diagnostics and process manufacturing. Are you interested in making a career in these? There are many AI certification courses, data science certification courses, and ML certifications available online. Check out! Read More

#artificial-intelligence, #data-science

How to Build a Machine Learning Model

A Visual Guide to Learning Data Science

Learning data science may seem intimidating but it doesn’t have to be that way. Let’s make learning data science fun and easy. So the challenge is how do we exactly make learning data science both fun and easy?

Cartoons are fun and since “a picture is worth a thousand words”, so why not make a cartoon about data science? With that goal in mind, I’ve set out to doodle on my iPad the elements that are required for building a machine learning model. Read More

#data-science, #machine-learning

Visualizing Vectors — Jed Crosby, Head of Data Science at Clari

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#data-science, #videos

Data Science, Quarantined

Companies are beginning to reboot their machine learning and analytics, which have been disrupted by the global pandemic.

The economic impact of COVID-19 is unprecedented, dramatically changing markets and prospects for economic growth. Supply chains, transportation, food processing, retail, e-commerce, and many other industries have transformed overnight. Unemployment in the U.S. has reached levels unknown in recent memory, and GDP is expected to fall around the world. As one economic journalist summed up the situation: “Nearly everything in the world is super-weird and disrupted right now.” Read More

#data-science

The 20 data science projects at the core of every successful business

What do you get if you draw a map linking the thirteen key business functions…

Marketing, Customer Services, Sales, R&D, Purchasing, Production, Distribution, IT, HR, Legal, Finance, Senior Management and Operations.

… to the three key elements of any business?… Read More

#data-science, #strategy

Why It’s So Freaking Hard To Make A Good COVID-19 Model

Here we are, in the middle of a pandemic, staring out our living room windows like aquarium fish. The question on everybody’s minds: How bad will this really get? Followed quickly by: Seriously, how long am I going to have to live cooped up like this?

We all want answers. And, given the volume of research and data being collected about the novel coronavirus, it seems like answers ought to exist. Read More

#data-science

Top 10 Free Ebooks To Learn Data Science

Data science is one collective term that is on everyone’s mouth these days, with its applications now being used across big companies, research institutes, and college projects. Since data science is utilised in every sector these days, it is crucial to have a sound knowledge of this vast subject. Although a wide range of information can be found on any search engine, the wiser step is to read materials that have been carefully penned down by experts from the field and are available in the form of e-Books.Data science is one collective term that is on everyone’s mouth these days, with its applications now being used across big companies, research institutes, and college projects. Since data science is utilised in every sector these days, it is crucial to have a sound knowledge of this vast subject. Although a wide range of information can be found on any search engine, the wiser step is to read materials that have been carefully penned down by experts from the field and are available in the form of e-Books. Read More

#books, #data-science