1 min read

    The Rise of the New FinTech Middle Man

    By Emily on Aug 17, 2020 1:34:29 PM

    As large banks embrace FinTech start-ups and their advanced technology rather than compete against them, both parties aim to eliminate the “middle man” in financial services transactions. This “middle man” is a metaphor for the different steps of customer interaction that technology has removed to make banking more efficient. However, in the hyper-speed environment from which bank - start-up integrations emerge, a new middle man - between these parties has become necessary.

    Topics: FinTech Startup Careers Bitcoin trends Blockchain
    2 min read

    InsurTech + Girl Power Hit Webster Hall For FinTech Startup Conference

    By Emily on Aug 17, 2020 1:34:20 PM

    Empire Startups, a thriving startup FinTech community, held it’s annual FinTech Conference on Tuesday, April 26 at concert venue Webster Hall.  The sold-out audience of 560 attendees consisted of early stage startups and larger companies in roughly equal proportion.

    Topics: FinTech events conference
    3 min read

    Data Science vs Machine Learning - Exploring the two paradigms

    By Kiran Datar on Aug 17, 2020 1:34:10 PM

    Data Science is the coveted new career around the block but not many can define the exact role of a data scientist. Being a relatively new field of work with people signing up for the role from different backgrounds, data science as a discipline requires a very broad skill set. Data mining, data analysis, machine learning, business analysis, data visualization, A/B testing are some of the skills a data scientist should have.

    Topics: Data Science
    3 min read

    Top 3 Ways Data Analytics Can Reduce Costs In Healthcare and Medicine

    By Sejal Gupta on Aug 17, 2020 1:34:00 PM

    Topics: Big Data healthcare smart device healthtech Data Science medtech
    1 min read

    Career Transition: Data Scientist Q&A

    By Byte on Aug 17, 2020 1:33:51 PM

    At Byte Academy, we teach a variety of courses within the field of Data Science. From our full-time immersive to our mini-courses in topics like Machine Learning and Data Visualization, we're consistently asked about what a career transition into Data Science looks like. To provide some guidance to our prospective students and blog readers, we've asked our own Data Scientist, Lesley Cordero, for her own perspective on frequently asked questions.

    Topics: syllabus law Careers Data Science
    5 min read

    Top 10 Datasets for Deep Learning

    By Manavika Phukan on Aug 17, 2020 1:33:34 PM

    The strength and robustness of a machine learning algorithm often lies in the quality of the dataset used to train it. Therefore, it would suffice to say that to gain true mastery within these fields, it is imperative that a person gains experience over a variety of machine learning problems that deal with a variety of datasets - ranging from image processing to speech recognition.

    Topics: Deep Learning Data Science
    5 min read

    The Worst Kind of Data: Missing Data

    By Uday Keith on Aug 17, 2020 1:33:23 PM

    Most publicly available datasets or datasets at the workplace are complete. However, from time to time we encounter datasets where some or many entries are missing. The problem of missing data exists on a spectrum; only a few entries missing among millions is virtually negligible, however, upwards of 10% of missing data can be crippling.

    The exact problem of missing data contains multiple layers, so let us proceed to peel it like the onion it is.  At its most basic, enough missing data may skew the distribution(s) the data follows.

    Topics: coding Data Science Programming Tips
    3 min read

    The Music Industry is Rapping to Data Science

    By Byte on Aug 17, 2020 1:33:13 PM

    From the Beatles to Taylor Swift, everyone's music is available digitally now. People used to think technology is killing the music industry, but it's technology which is reviving it. So for musicians who are also interested in programming, data science is one way to get onboard with the idea. Spotify and Pandora know just the right track to play next thanks to data science. Wondering which song did well and why, look no further, the answer is in data science.

     

    Pandora was perhaps the frontrunner of combining the two when it started the 'Music Genome Project' way back in 1999 before terms like Big Data even existed. The project considers songs as datasets and analyzes each song using up to 450 distinct musical characteristics or “genes”. A person – a trained music analyst with an actual degree in music – and automated algorithms comb through the song and classify it as Pop/Rock, Hip-Hop/Electronica, Jazz, World Music, and Classical. Decoding the “genes” of the song helps Pandora find the similarities and then successfully predict what a user might like listening to next.

    Topics: Big Data spotify Careers music Data Science
    5 min read

    The Beautiful Binomial Logistic Regression

    By Uday Keith on Aug 17, 2020 1:32:57 PM

    The Logistic Regression is an important classification model to understand in all its complexity. There are a few reasons to consider it:

    Topics: regression Data Science
    1 min read

    The 16 FinTech Unicorns Only Do Three Things

    By Byte on Aug 17, 2020 1:32:45 PM

    Will this breakdown remain, or will the market get too heavy in those sectors and even out?

    Topics: Uncategorized

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