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All Blog Posts Tagged 'learning' (212)

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

Sentiment Analysis: Types, Tools, and Use Cases

What do you do before purchasing something that costs more than a pack of gum? Whether you want to treat yourself to new sneakers, a laptop, or an overseas tour, processing an order without checking out similar products or offers and reading reviews doesn’t make much sense anymore. Thanks to comment sections on eCommerce sites, social nets, review platforms, or dedicated forums, you can learn a ton about a product or service and evaluate whether it’s a good value for money. Other customers,…

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Added by Kateryna Lytvynova on October 30, 2018 at 12:45am — No Comments

How to be an Artificial Intelligence (AI) Expert?

Introduction

Artificial Intelligence is growing at a rapid pace in the last decade. You have seen it all unfold before your eyes. From self-driving cars to Google Brain, artificial intelligence has been at the centre of these amazing huge-impact projects.

Artificial Intelligence (AI) made headlines recently when people started reporting that Alexa was laughing unexpectedly. Those news reports led to the usual…

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Added by Divya Singh on October 29, 2018 at 7:30am — 1 Comment

Facial Recognition and its Applications

Facial Recognition

Facial recognition technology was always a mythical concept that we thought could be a tool that could solve many of our problems but would never see the light of day. Today, facial recognition is everywhere and is a part of the everyday technology that we use. The…

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Added by Abhimanyu on October 25, 2018 at 12:50am — No Comments

The Case for Just Getting Your Feet Wet with AI

Summary:  Even if you’re not big enough to have a full blown data science group that shouldn’t hold you back from benefiting from AI.  The market has evolved so that there are now industry and process specific vertical applications available from 3rd party AI vendors that you can implement.  There are just a few things to look out for.

 …

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Added by William Vorhies on October 23, 2018 at 7:30am — No Comments

88 Resources & Tools to Become a Data Scientist

Harvard Business Review has regareded data scientist as the sexiest job of the 21st century. In this article, with the assistance of Octoparse V7, we aggregated the resources and tools that you may need to become a data scientist.

1.…

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Added by Paul Black on October 9, 2018 at 5:30pm — 1 Comment

Practicing ‘No Code’ Data Science

Summary:  We are entering a new phase in the practice of data science, the ‘Code-Free’ era.  Like all major changes this one has not sprung fully grown but the movement is now large enough that its momentum is clear.  Here’s what you need to know.

 

We are entering a new phase in the practice of data science, the ‘Code-Free’…

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Added by William Vorhies on October 9, 2018 at 9:54am — 3 Comments

Python Vs R : The Eternal Question for Data Scientists

Python and R are the two most commonly used languages for data science today. They are both fully open source products and completely free to use and modify as required under the GNU public license.

But which one is better? And, more importantly, which one should you learn?

Both are widely used and are standard tools in the hands of every data scientist.

The answer may surprise you – because as a professional data scientist, you should be ready to deal with…

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Added by Divya Singh on October 2, 2018 at 6:15am — 1 Comment

Data Science Glossary

There has been much hype surrounding deep learning and data science learning in recent times, and one of the cornerstones of deep learning is the neural network. In this article, we will look at what a neural network is and get familiar with the relevant terminologies.

In simplest terms, a neural network is an interconnection of neurons. Now the question arises, what is a neuron? To understand neurons in deep learning, we first…

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Added by Divya Singh on September 20, 2018 at 4:00am — No Comments

Comparing Machine Learning as a Service: Amazon, Microsoft Azure, Google Cloud AI, IBM Watson

planets

For most businesses, machine learning seems close to rocket science, appearing expensive and talent demanding. And, if you’re aiming at building another Netflix recommendation system, it really is. But the trend of making everything-as-a-service has affected this sophisticated sphere, too. You can jump-start an ML initiative without much investment, which would be the right move if you are new to data science and just want to grab the low hanging fruit.

One of ML's…

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Added by Olexander Kolisnykov on September 18, 2018 at 2:52am — No Comments

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