Blog

The sense behind the data

In the world of data we are surfing, one of the most relevant things is to have a clear overview about what you are looking for to do the right questions. Having a huge amount of data could be nothing without sense, so giving sense to the data is more important than having data. The…
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Difference between Machine Learning and Deep Learning

Machine Learning (ML) is a subset of Artificial Intelligence. It is a method of training an algorithm with data (input) in order to get the desired output without explicitly programming it to do so. ML is simply a technique for realizing AI. Deep Learning (DL) is considered a subset of Machine Learning. This has to…
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ML vs DL

Machine Learning modifies an algorithm without any human intervention by using structured data. Deep Learning, on the other hand, tries to imitate the human brain by using artificial neurons that form different interpretations of the same data. Based on these interpretations the best possible answer is arrived at. In simple words, if a Machine learning…
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Kate Strachnyi’s 20 Books for 2020

Part of my goal for the year is to read twenty books. Below is a list of the books that I can’t wait to get my hands on! AUDIO BOOKS 50/50: Secrets I Learned Running 50 Marathons in 50 Days — and How You Too Can Achieve Super Endurance! Dean Karnazes AI Superpowers: China, Silicon…
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20 SMART Goals for 2020

There are several things I’d like to accomplish next year. Below, I share my 20 SMART goals for 2020: 365 days of Python & R code – follow this hashtag #dailycoding – posting learning progress on social media Help 20 companies with their social media strategy (focused on companies innovating in the data science and artificial intelligence…
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ODSC WEST 2019 RECAP

Brief recap of the Open Data Science Conference – San Francisco, October 2019 On AI ROI: the questions you need to be asking Kerstin Frailey Metis Success is unpredictable in AI – feasibility is often unknown before a project has begun. Projects are esoteric – require highly specialized training. Application is new – methods to…
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2019 Year in Review – Kate Strachnyi

Link to video of 2019 Year in Review January Launched the Datacated Weekly challenge – close to 300 posts Started the Online Book Club – LinkedIn Group – over 1,500 members Story by Data became a Community Partner with ODSC February Vacation to Dominican Republic Joined the IADSS Advisory Board First ultra-marathon (50k trail run)…
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5 Reasons to Learn R Programming

Over the past 5 years, I’ve mainly relied on using data visualization tools (i.e. Tableau) to satisfy my data analytics needs. In recent months, I’ve focused on learning more about computer programming and am exploring various languages, such as Python and R. I believe that both languages are useful and can be effective in their own…
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20 Data Trends for 2020

Though we cannot tell what the future holds for us, we can make predictions based on trends. Read about the key data trends from twenty thought-leaders for 2020. JT Kostman Ph.D – A global cyber crime pandemic ($6T annually) and an ever-expanding alphabet soup of data privacy/protection legislation will increasingly require Data Scientists to accept…
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