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All Blog Posts Tagged 'learning' (225)

Text Encoding: A Review

The key to perform any text mining operation, such as topic detection or sentiment analysis, is to transform words into numbers, sequences of words into sequences of numbers. Once we have numbers, we are back in the well-known game of data analytics, where machine learning algorithms can help us with classifying and clustering.

We will focus here exactly on that part of the analysis that transforms words…

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Added by Rosaria Silipo on February 11, 2019 at 3:09pm — No Comments

One Shot Learning and Other Strategies for Reducing Training Data

Summary: Not enough labeled training data is a huge barrier to getting at the equally large benefits that could be had from deep learning applications.  Here are five strategies for getting around the data problem including the latest in One Shot Learning.

 

For at least the last two years we’ve been in an…

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Added by William Vorhies on January 28, 2019 at 9:56am — 1 Comment

Machine Learning for Transactional Analytics: Customer Life time Value v/s Acquisition Cost

Understanding customer transactional behaviour pays well for any business. With the tsunami of start ups in recent times and the immense money flow in businesses, customers find lucrative offers from companies for acquisition, retention & referrals strategies. Understanding transactional behaviour of a customer has become even more complex with the invent of new business houses everyday. Although, with the rise of powerful machines, one can…

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Added by PS Dhillon on January 28, 2019 at 4:00am — No Comments

Doctors are from Venus, Data Scientists from Mars – or Why AI/ML is Moving so Slowly in Healthcare

Summary: The world of healthcare may look like the most fertile field for AI/ML apps but in practice it’s fraught with barriers.  These range from cultural differences, to the failure of developers to really understand the environment they are trying to enhance, to regulatory and logical Catch 22s that work against adoption.  Part 3 of 3.

 …

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Added by William Vorhies on January 21, 2019 at 7:59am — 2 Comments

The AI/ML Opportunity Landscape in Healthcare. Do It Right or It Will be More of a Mine Field.

Summary:  Despite hundreds of projects and thousands of data scientists devoted to bringing AI/ML to healthcare, adoption remains low and slow.  A good portion of this problem is our own fault for failing to see the processes being disrupted through the eyes of the physician users.  Here we lay out the healthcare opportunity landscape but for data scientists following classical disruption strategies, it may be more of a minefield.  Part 2 of…

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Added by William Vorhies on January 14, 2019 at 8:00am — No Comments

Deep Learning picking momentum in option pricing and financial risk management

Deep Learning is picking momentum in Quantitative Finance, outside the obvious application to the prediction of asset prices (where to my knowledge it is not particularly effective) and spreading into the more serious application area of option pricing and risk management.

These two recent papers clearly demonstrate the benefits of DL as a pricing technology alternative to the classical FDM and Monte-Carlo in certain contexts:…

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Added by Antoine Savine on January 11, 2019 at 5:30am — No Comments

New Similarity Methods for Unsupervised Machine Learning

1. Introduction

Data science is changing the rules of the game for decision making. Artificial intelligence is living its golden years where abundance of data, cheap computing capacity, and devoted talent depicts an unstoppable intelligence assisted life for humans. While it is common to hear about AI advice on health or financial investments, the same in business strategy is not so common. Maybe it is just a matter of time that AI learns how to handle data to support…

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Added by Ramon Serrallonga on January 9, 2019 at 9:00am — 3 Comments

Seeing the AI/ML Future in Healthcare Through the Eyes of Physicians. It Doesn’t Look Quite the Way Data Scientists See It.

Summary: If you want to understand the promise of AI/ML in healthcare you need to see it through the eyes of physicians, the ultimate users.  Turns out these folks aren’t the rapid adopters you’d think they’d be and the problem is largely with the way data scientists have tried to implement.  Part 1 of 3.

 

It’s…

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Added by William Vorhies on January 7, 2019 at 8:00am — 4 Comments

The Ultimate R Cheat Sheet - Major Upgrade

The Ultimate R Cheat Sheet simply put makes it easy to learn R. The Ultimate R Cheat Sheet saves you time by providing hyperlinks to the documentation and package-level cheat sheets for the most important packages in R. The latest update doubles its ultimateness by providing a second page that includes Special Topics:

  • Time Series, Forecasting, and Financial…

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Added by Matt Dancho on January 7, 2019 at 3:00am — No Comments

Comparison of the Text Distance Metrics

Measuring the similarity between texts is a common task in many applications. It is useful in classic NLP fields like search, as well as in such far from NLP areas as medicine and genetics. There are many different approaches of how to compare two texts (strings of characters). Each has its own advantages and disadvantages and is good only…

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Added by Igor Bobriakov on January 4, 2019 at 12:30am — No Comments

High Density Region Estimation with KernelML

Data scientists and predictive modelers often use 1-D and 2-D aggregate statistics for exploratory analysis, data cleaning, and feature creation. Higher dimensional aggregations, i.e., 3 dimensional and above, are more difficult to visualize and understand. High density regions are one example of these N-dimensional statistics. High density regions can be useful for summarizing common characteristics across multiple variables. Another use case is to validate a forecast prediction’s…

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Added by Rohan Kotwani on January 3, 2019 at 4:00pm — No Comments

How to Choose Fraud Detection Software: Features, Characteristics, Key Providers

As we make more cashless payments for retail purchases, restaurants, and transportation – not to mention the increase in online shopping – wallets loaded with legal tender may become a thing of the past. According to 2018 research by BigCommerce, software vendor and Square payment processing solution provider, 51 percent of Americans think that online shopping is the best option. Last year, 1.66 billion people worldwide bought goods online. And the…

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Added by Kateryna Lytvynova on December 19, 2018 at 1:00am — No Comments

The complete manuscript of The Hundred-Page Machine Learning Book is now online

The drafts of the two final chapters of The Hundred-Page Machine Learning Book are now online. They consider metric learning, learning to rank, learning to recommend (including factorization machines and denoising autoencoders), and word embeddings.

The book is now complete and I'm so happy about…

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Added by Andriy Burkov on December 17, 2018 at 12:41pm — No Comments

5 Predictions about Data Science, Machine Learning, and AI for 2019

Summary:  Here are our 5 predictions for data science, machine learning, and AI for 2019.  We also take a look back at last year’s predictions to see how we did.

 

It’s that time of year again when we do a look back in order to offer a look forward.  What trends will speed up, what things will actually happen,…

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Added by William Vorhies on December 17, 2018 at 8:50am — No Comments

Firms can save time and cost with Deep learning methodologies!

The rise in Machine Learning, Deep Learning and Artificial Intelligence technologies seems to breaking all barriers. All these technologies have the potential to spur innovation everywhere in the world. When it comes to deep learning, the technological advancement seem to be very uplifting. They have the power to help the companies perform better and more quickly. But, at the same time, there is certain amount of confusion surrounding these technologies as well.…

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Added by Samual Alister on December 7, 2018 at 5:00am — No Comments

Python Multi-Threading vs Multi-Processing

There is a library called threading in Python and it uses threads (rather than just processes) to implement parallelism. This may be surprising news if you know about the Python's Global Interpreter Lock, or GIL, but it actually works well for certain instances without violating the GIL. And this is all done without any overhead -- simply define…

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Added by Michael Li on November 29, 2018 at 6:30am — 1 Comment

The Two (Conflicting) Definitions of AI

Summary:  There are two definitions currently in use for AI, the popular definition and the data science definition and they conflict in fundamental ways.  If you’re going to explain or recommend AI to a non-data scientist, it’s important to understand the difference.

 

For a profession as concerned with accuracy as we are, we do a really poor job at naming things, or at least being consistent in the naming.  “Big Data” – totally misleading…

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Added by William Vorhies on November 27, 2018 at 8:23am — No Comments

Things that Aren’t Working in Deep Learning

Summary:  This may be the golden age of deep learning but a lot can be learned by looking at where deep neural nets aren’t working yet.  This can be a guide to calming the hype.  It can also be a roadmap to future opportunities once these barriers are behind us.

 

We are living in the golden age of deep…

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Added by William Vorhies on November 18, 2018 at 11:14am — No Comments

Speedup your Machine Learning applications without changing your code

Emerging cloud applications like machine learning, AI and big data analytics require high performance computing systems that can sustain the increased amount of data processing without consuming excessive power. Towards this end, many cloud operators have started adopting heterogeneous infrastructures deploying hardware accelerators, like FPGAs, to increase the performance of computational intensive tasks. However, most hardware accelerators lack…

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Added by Chris Kachris on November 6, 2018 at 7:00am — 2 Comments

The Best Opportunities in AI for Data Scientists

Summary:  Looking for your next job in an early stage company but want to make sure your startup has staying power.  Follow the expert rankings by CB Insights that also show us the changing trends in how AI startups should be focusing their offerings.

 

Let’s suppose you’re early in your data science career and your credentials…

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Added by William Vorhies on November 5, 2018 at 4:18pm — No Comments

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