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10 Notable Frameworks for NLP
Natural Language Processing hit its big stride back in 2017 with the introduction of Transformer Architecture from Google. State of the art approaches helped bridge the gap between humans and machines and helped us build bots capable of using human language undetected. It’s an exciting time. You’re going to... Read more
5 Deep Learning Frameworks to Consider for 2020
Enough of flirting with deep learning and deep learning frameworks; it’s time to glide across the room and say, “Hello.” Call it an advanced subfield of machine learning or future to enhanced vision in the field of technology, deep learning won’t stop now!  Imbibed in the majority of business... Read more
Major Updates to the Most Popular Data Science Frameworks in 2019
This time last year we brought you a detailed report of all the important updates for popular data science (machine learning and deep learning) frameworks throughout 2018. The developers of these frameworks continue to innovate at an accelerated rate. Data scientists demand more powerful tools in order to get... Read more
Top 7 Machine Learning Frameworks for 2020
Machine learning is a nightmare without some kind of structure. You can’t build everything from scratch, especially if you’re in a business setting. Even if you want to (and if you do, comment here and tell us about it!), you don’t have time in most cases. You need a... Read more
Deep Learning Frameworks You Need to Know in 2020
Deep learning networks have a mind-boggling ability to learn, so training these models requires massive computing power and intense amounts of data. You’ll need a framework to make that development easier. Deep learning requires massive processing power and lots of data. Because it uses unstructured, often non-text based data, you’ll... Read more
Using Keras and TensorFlow in R
Keras and Tensorflow are two very powerful packages that are normally accessed via python. Since the packages were developed for python they may have the illusion of being out of reach for R users. However, this is not the case as the Keras and Tensorflow packages may be set... Read more
Announcing the ODSC West 2019 Data Science Award Winners
ODSC was started with a desire to build a community around data science and to make it more accessible. Sheamus McGovern, the founder of ODSC, said: “in this attempt, we owe a debt of gratitude .” Open source work is really the backbone of... Read more
Software 2.0 and Snorkel: Beyond Hand-Labeled Data
This ODSC West 2018 talk “Software 2.0 and Snorkel: Beyond Hand-Labeled Data,” presented by Alex Ratner, a Ph.D. student in Computer Science at Stanford University, discusses a new way of effectively programming machine learning systems using what’s called “weaker supervision,” and how it enables domain experts who don’t know... Read more
Using an Embedding Matrix on Tabular Data in R
How would you tackle the prospects of representing a categorical feature, with 100’s of levels, in a model? A first approach may be to create a one-hot encoded matrix representing each level of the feature. The result would be a large and sparse matrix where the majority of the... Read more
Deep Learning with TensorFlow 2.0
Editor’s Note: See Jon’s talk “Deep Learning with TensorFlow 2.0” at ODSC West 2019.  This summer, I had a blast speaking at Immersive A.I.—the first annual Open Data Science Conference (ODSC) event in New York. The venue was flawless, the organizers were exceptionally well-prepared, and there was a remarkable... Read more