Learning With Data

// Learning With Data

Oct 20
Machine learning: introduction, monumental failure, and hope
Photo by Ahmed Hasan on Unsplash What is Machine Learning? Wikipedia tells us that Machine learning is, “a field of computer science that gives computers the ability to learn without being explicitly programmed.” It goes on to say, “machine learning explores the study and construction of algorithms that can learn from and make predictions on data — such algorithms overcome following strictly static program instructions by making data-driven predictions or decisions, through building a model from sample inputs.
Oct 17
How To Maximize the Value of Your Next Conference and Stop Wasting Your Time
Photo by Product School on Unsplash I am currently in London as a speaker for the Ignite AI event of the O’Reilly Artificial Intelligence conference. Before attending the conference, I thought a lot about how to not waste my time here. I believe that many others working in technology also wonder about how to make sure attending a conference is worth their time. Here are some of my thoughts. Speak The best way to get value from a conference is to speak at the conference.
Oct 15
Shh…The Secret to Building Great AI
I apologize for the somewhat clickbait title, but I just had to create the meme above after seeing Elon Musk’s tweet: I thought that was hilarious…anyways, back to your regular programming. When you finish a PhD in machine learning, they take you to a special room and explain that great data is way more important than all the fancy math and algorithms you just learned At least, that is how I imagine it.
Oct 13
My 5 Favorite Data Science Portfolios
Photo by Aziz Acharki on Unsplash Earlier this week, I posted an article on How to Create an Amazing Data Science Portfolio: How to Create an Amazing Data Science Portfolio _To showcase your work and stand out_towardsdatascience.com At the end of the article, I posted a link to an example portfolio that I liked by Tim Dettmers. Afterward, I had a few people ask me to compile a larger list of great data science portfolios and projects.
Oct 9
How to Create an Amazing Data Science Portfolio
Photo by Skye Studios on Unsplash Recently, I wrote an article with advice for breaking into the field of data science. If you are interested, you can check out the article here: Standing Out in a Sea of Data Scientists _Advice for breaking into the field of data science_towardsdatascience.com One of the pieces of advice was to “gain experience defining and solving a problem with machine learning from end-to-end.” I’ve had some questions on how to do this effectively, so I would love to dig in a bit deeper on how I would essentially begin to build a data science portfolio.
Oct 5
Delivering on the Promise of Artificial Intelligence
Photo by Alex Knight on Unsplash You keep hearing about Artificial Intelligence (AI). Nvidia’s CEO says, “AI is going to eat software.” Mark Cuban exclaims, “Artificial Intelligence, deep learning, machine learning — whatever you’re doing if you don’t understand it — learn it. Because otherwise, you’re going to be a dinosaur within 3 years.” And yet, at the same time, you read articles about companies failing to execute with AI. Some even claim that 85% of efforts fail.
Oct 2
Overcoming Your Fear of Research Papers
Source: https://www.pexels.com/ Let’s be honest — research papers are scary. In the field of machine learning, reading a research paper can feel like staring into an abyss of dense words and complicated formulas. It can be very easy to look into that abyss and assume it is too much to overcome. Learning how to extract information from research papers, though, is critical. The field of machine learning is moving so quickly that often the only way to stay up to date is by reading papers.
Sep 28
An Often Overlooked Data Science Skill
Source: Pexels You have just started your first job as a data scientist and you are excited to start using your random forest skills to actually make a difference. You get all setup — primed to start your Jupyter Notebook — only to realize you first need to “SSH” into a different machine to run your models. The company leverages cloud computing in order to execute on machine learning at scale.
Sep 25
Standing Out in a Sea of Data Scientists
Source: Pexels For 2019, Glassdoor ranked data scientist as the number one best job in America. The ever-growing popularity of the data science career path has led to an explosion in degrees, programs, and bootcamps targeted at people looking to enter the field. According to Discover Data Science a bachelors degree in data science was nearly non-existent 5 years ago and now there are over 50. While demand for data scientists continues to grow (Indeed reported a 29% increase in demand from 2018 to 2019), I would argue that landing your first job as a data scientist is perhaps harder than ever due to the increased supply of entry-level talent.