Search results for NLP
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Resources For Women In Data Science and Machine Learning
A comprehensive list of resources for Women in Data Science and Machine Learning, including a list of useful tech groups and published lists for finding Women speakers.https://www.kdnuggets.com/2018/06/resources-women-data-science-machine-learning.html
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On the contribution of neural networks and word embeddings in Natural Language Processing
In this post I will try to explain, in a very simplified way, how to apply neural networks and integrate word embeddings in text-based applications, and some of the main implicit benefits of using neural networks and word embeddings in NLP.https://www.kdnuggets.com/2018/05/contribution-neural-networks-word-embeddings-natural-language-processing.html
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10 More Free Must-Read Books for Machine Learning and Data Science">10 More Free Must-Read Books for Machine Learning and Data Science
Summer, summer, summertime. Time to sit back and unwind. Or get your hands on some free machine learning and data science books and get your learn on. Check out this selection to get you started.https://www.kdnuggets.com/2018/05/10-more-free-must-read-books-for-machine-learning-and-data-science.html
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If chatbots are to succeed, they need this
Can logic be used to make chatbots intelligent? In the 1960s this was taken for granted. Now we have all but forgotten the logical approach. Is it time for a revival?https://www.kdnuggets.com/2018/05/chatbots-succeed-need-logic.html
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How to Organize Data Labeling for Machine Learning: Approaches and Tools
The main challenge for a data science team is to decide who will be responsible for labeling, estimate how much time it will take, and what tools are better to use.https://www.kdnuggets.com/2018/05/data-labeling-machine-learning.html
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A Brief Introduction to Wikidata
Like Wikipedia, there are all kinds of data stored in Wikidata. As such, when you are looking for a specific dataset or if you want to answer a curious question, it can be a good start looking for that data at Wikidata first.https://www.kdnuggets.com/2018/05/brief-introduction-wikidata.html
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Apache Spark : Python vs. Scala">Apache Spark : Python vs. Scala
When it comes to using the Apache Spark framework, the data science community is divided in two camps; one which prefers Scala whereas the other preferring Python. This article compares the two, listing their pros and cons.https://www.kdnuggets.com/2018/05/apache-spark-python-scala.html
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AI is not set and forget
Just like a car, AI-based system can tick along in decent shape for a while. But neglect it too long and you’re in trouble. Unfortunately, failing to maintain your AI will destroy the project.https://www.kdnuggets.com/2018/05/ai-not-set-forget.html
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To Kaggle Or Not
Kaggle is the most well known competition platform for predictive modeling and analytics. This article looks into the different aspects of Kaggle and the benefits it can bring to data scientists.https://www.kdnuggets.com/2018/05/to-kaggle-or-not.html
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Getting Started with spaCy for Natural Language Processing
spaCy is a Python natural language processing library specifically designed with the goal of being a useful library for implementing production-ready systems. It is particularly fast and intuitive, making it a top contender for NLP tasks.https://www.kdnuggets.com/2018/05/getting-started-spacy-natural-language-processing.html
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50+ Useful Machine Learning & Prediction APIs, 2018 Edition">50+ Useful Machine Learning & Prediction APIs, 2018 Edition
Extensive list of 50+ APIs in Face and Image Recognition ,Text Analysis, NLP, Sentiment Analysis, Language Translation, Machine Learning and prediction.https://www.kdnuggets.com/2018/05/50-useful-machine-learning-prediction-apis-2018-edition.html
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Implementing Deep Learning Methods and Feature Engineering for Text Data: The GloVe Model
The GloVe model stands for Global Vectors which is an unsupervised learning model which can be used to obtain dense word vectors similar to Word2Vec.https://www.kdnuggets.com/2018/04/implementing-deep-learning-methods-feature-engineering-text-data-glove.html
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Top Stories, Apr 16-22: 7 Books to Grasp Mathematical Foundations of Data Science and Machine Learning; Python Regular Expressions Cheat Sheet
Also: Key Algorithms and Statistical Models for Aspiring Data Scientists; Why Deep Learning is perfect for NLP; Derivation of Convolutional Neural Network from Fully Connected Network Step-By-Step; Top 8 Free Must-Read Books on Deep Learninghttps://www.kdnuggets.com/2018/04/top-news-week-0416-0422.html
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Understanding What is Behind Sentiment Analysis – Part 2
Fine-tuning our sentiment classifier...https://www.kdnuggets.com/2018/04/understanding-behind-sentiment-analysis-part-2.html
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Key Algorithms and Statistical Models for Aspiring Data Scientists">Key Algorithms and Statistical Models for Aspiring Data Scientists
This article provides a summary of key algorithms and statistical techniques commonly used in industry, along with a short resource related to these techniques.https://www.kdnuggets.com/2018/04/key-algorithms-statistical-models-aspiring-data-scientists.html
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Top 10 Technology Trends of 2018">Top 10 Technology Trends of 2018
In this article, we will focus on the modern trends that took off well on the market by the end of 2017 and discuss the major breakthroughs expected in 2018.https://www.kdnuggets.com/2018/04/top-10-technology-trends-2018.html
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Understanding What is Behind Sentiment Analysis – Part 1
Build your first sentiment classifier in 3 steps.https://www.kdnuggets.com/2018/04/understanding-behind-sentiment-analysis-part-1.html
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Ten Machine Learning Algorithms You Should Know to Become a Data Scientist">Ten Machine Learning Algorithms You Should Know to Become a Data Scientist
It's important for data scientists to have a broad range of knowledge, keeping themselves updated with the latest trends. With that being said, we take a look at the top 10 machine learning algorithms every data scientist should know.https://www.kdnuggets.com/2018/04/10-machine-learning-algorithms-data-scientist.html
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Why so many data scientists are leaving their jobs">Why so many data scientists are leaving their jobs
We look at some of the big challenges and frustrations that data scientists face on a regular basis.https://www.kdnuggets.com/2018/04/why-data-scientists-leaving-jobs.html
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A Day in the Life of a Data Scientist: Part 4
Interested in what a data scientist does on a typical day of work? Each data science role may be different, but these contributors have insight to help those interested in figuring out what a day in the life of a data scientist actually looks like.https://www.kdnuggets.com/2018/04/day-life-data-scientist-part-4.html
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Understanding Feature Engineering: Deep Learning Methods for Text Data
Newer, advanced strategies for taming unstructured, textual data: In this article, we will be looking at more advanced feature engineering strategies which often leverage deep learning models.https://www.kdnuggets.com/2018/03/understanding-feature-engineering-deep-learning-methods-text-data.html
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Text Data Preprocessing: A Walkthrough in Python">Text Data Preprocessing: A Walkthrough in Python
This post will serve as a practical walkthrough of a text data preprocessing task using some common Python tools.https://www.kdnuggets.com/2018/03/text-data-preprocessing-walkthrough-python.html
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5 Things You Need to Know about Sentiment Analysis and Classification">5 Things You Need to Know about Sentiment Analysis and Classification
We take a look at the important things you need to know about sentiment analysis, including social media, classification, evaluation metrics and how to visualise the results.https://www.kdnuggets.com/2018/03/5-things-sentiment-analysis-classification.html
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Creating a simple text classifier using Google CoLaboratory
Google CoLaboratory is Google’s latest contribution to AI, wherein users can code in Python using a Chrome browser in a Jupyter-like environment. In this article I have shared a method, and code, to create a simple binary text classifier using Scikit Learn within Google CoLaboratory environment.https://www.kdnuggets.com/2018/03/simple-text-classifier-google-colaboratory.html
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Text Processing in R
There are good reasons to want to use R for text processing, namely that we can do it, and that we can fit it in with the rest of our analyses. Furthermore, there is a lot of very active development going on in the R text analysis community right now.https://www.kdnuggets.com/2018/03/text-processing-r.html
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5 Fantastic Practical Natural Language Processing Resources
This post presents 5 practical resources for getting a start in natural language processing, covering a wide array of topics and approaches.https://www.kdnuggets.com/2018/02/5-fantastic-practical-natural-language-processing-resources.html
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Resurgence of AI During 1983-2010
We discuss supervised learning, unsupervised learning and reinforcement learning, neural networks, and 6 reasons that helped AI Research and Development to move ahead.https://www.kdnuggets.com/2018/02/resurgence-ai-1983-2010.html
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Neural network AI is simple. So… Stop pretending you are a genius">Neural network AI is simple. So… Stop pretending you are a genius
This post may come off as a rant, but that’s not so much its intent, as it is to point out why we went from having very few AI experts, to having so many in so little time.https://www.kdnuggets.com/2018/02/neural-network-ai-simple-genius.html
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The Birth of AI and The First AI Hype Cycle
A dazzling review of AI History, from Alan Turing and Turing Test, to Simon and Newell and Logic Theorist, to Marvin Minsky and Perceptron, birth of Rule-based systems and Machine Learning, Eliza - first chatbot, Robotics, and the bust which led to first AI Winter.https://www.kdnuggets.com/2018/02/birth-ai-first-hype-cycle.html
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Top 15 Scala Libraries for Data Science in 2018
For your convenience, we have prepared a comprehensive overview of the most important libraries used to perform machine learning and Data Science tasks in Scala.https://www.kdnuggets.com/2018/02/top-15-scala-libraries-data-science-2018.html
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Understanding Learning Rates and How It Improves Performance in Deep Learning
Furthermore, the learning rate affects how quickly our model can converge to a local minima (aka arrive at the best accuracy). Thus getting it right from the get go would mean lesser time for us to train the model.https://www.kdnuggets.com/2018/02/understanding-learning-rates-improves-performance-deep-learning.html
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Training and Visualising Word Vectors
In this tutorial I want to show how you can implement a skip gram model in tensorflow to generate word vectors for any text you are working with and then use tensorboard to visualize them.https://www.kdnuggets.com/2018/01/training-visualising-word-vectors.html
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Comparing Machine Learning as a Service: Amazon, Microsoft Azure, Google Cloud AI">Comparing Machine Learning as a Service: Amazon, Microsoft Azure, Google Cloud AI
A complete and unbiased comparison of the three most common Cloud Technologies for Machine Learning as a Service.https://www.kdnuggets.com/2018/01/mlaas-amazon-microsoft-azure-google-cloud-ai.html
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Elasticsearch for Dummies
In this blog, you’ll get to know the basics of Elasticsearch, its advantages, how to install it and indexing the documents using Elasticsearch.https://www.kdnuggets.com/2018/01/elasticsearch-overview.html
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Beyond Word2Vec Usage For Only Words
A good example on how to use word2vec in order to get recommendations fast and efficiently.https://www.kdnuggets.com/2018/01/beyond-word2vec-for-words.html
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Machine Learning & Artificial Intelligence: Main Developments in 2017 and Key Trends in 2018">Machine Learning & Artificial Intelligence: Main Developments in 2017 and Key Trends in 2018
As we bid farewell to one year and look to ring in another, KDnuggets has solicited opinions from numerous Machine Learning and AI experts as to the most important developments of 2017 and their 2018 key trend predictions.https://www.kdnuggets.com/2017/12/machine-learning-ai-main-developments-2017-key-trends-2018.html
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Best Masters in Data Science and Analytics – Asia and Australia Edition
The fourth edition of our comprehensive, unbiased survey on graduate degrees in Data Science and Analytics from around the world.https://www.kdnuggets.com/2017/12/best-masters-data-science-analytics-asia-australia.html
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Using Deep Learning to Solve Real World Problems">Using Deep Learning to Solve Real World Problems
Do you assume that deep learning is only being used for toy problems and in self-learning scenarios? This post includes several firsthand accounts of organizations using deep neural networks to solve real world problems.https://www.kdnuggets.com/2017/12/using-deep-learning-solve-real-world-problems.html
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A General Approach to Preprocessing Text Data
Recently we had a look at a framework for textual data science tasks in their totality. Now we focus on putting together a generalized approach to attacking text data preprocessing, regardless of the specific textual data science task you have in mind.https://www.kdnuggets.com/2017/12/general-approach-preprocessing-text-data.html
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Understanding Deep Convolutional Neural Networks with a practical use-case in Tensorflow and Keras">Understanding Deep Convolutional Neural Networks with a practical use-case in Tensorflow and Keras
We show how to build a deep neural network that classifies images to many categories with an accuracy of a 90%. This was a very hard problem before the rise of deep networks and especially Convolutional Neural Networks.https://www.kdnuggets.com/2017/11/understanding-deep-convolutional-neural-networks-tensorflow-keras.html
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Natural Language Processing Library for Apache Spark – free to use
Introducing the Natural Language Processing Library for Apache Spark - and yes, you can actually use it for free! This post will give you a great overview of John Snow Labs NLP Library for Apache Spark.https://www.kdnuggets.com/2017/11/natural-language-processing-library-apache-spark.html
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Building a Wikipedia Text Corpus for Natural Language Processing
Wikipedia is a rich source of well-organized textual data, and a vast collection of knowledge. What we will do here is build a corpus from the set of English Wikipedia articles, which is freely and conveniently available online.https://www.kdnuggets.com/2017/11/building-wikipedia-text-corpus-nlp.html
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A Framework for Approaching Textual Data Science Tasks">A Framework for Approaching Textual Data Science Tasks
Although NLP and text mining are not the same thing, they are closely related, deal with the same raw data type, and have some crossover in their uses. Let's discuss the steps in approaching these types of tasks.https://www.kdnuggets.com/2017/11/framework-approaching-textual-data-tasks.html
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Tips for Getting Started with Text Mining in R and Python
This article opens up the world of text mining in a simple and intuitive way and provides great tips to get started with text mining.https://www.kdnuggets.com/2017/11/getting-started-text-mining-r-python.html
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Top 10 Machine Learning Algorithms for Beginners">Top 10 Machine Learning Algorithms for Beginners
A beginner's introduction to the Top 10 Machine Learning (ML) algorithms, complete with figures and examples for easy understanding.
https://www.kdnuggets.com/2017/10/top-10-machine-learning-algorithms-beginners.html
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7 Types of Artificial Neural Networks for Natural Language Processing">7 Types of Artificial Neural Networks for Natural Language Processing
What is an artificial neural network? How does it work? What types of artificial neural networks exist? How are different types of artificial neural networks used in natural language processing? We will discuss all these questions in the following article.https://www.kdnuggets.com/2017/10/7-types-artificial-neural-networks-natural-language-processing.html
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An Overview of 3 Popular Courses on Deep Learning">An Overview of 3 Popular Courses on Deep Learning
After completing the 3 most popular MOOCS in deep learning from Fast.ai, deeplearning.ai/Coursera (which is not completely released) and Udacity, I believe a post about what you can expect from these 3 courses will be useful for future Deep learning enthusiasts.https://www.kdnuggets.com/2017/10/3-popular-courses-deep-learning.html
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Data Science –The need for a Systems Engineering approach
We need a greater emphasis on the Systems Engineering aspects of Data Science. I am exploring these ideas as part of my course "Data Science for Internet of Things" at the University of Oxford.https://www.kdnuggets.com/2017/10/data-science-systems-engineering-approach.html
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Meet Lucy: Creating a Chatbot Prototype
This article walks you through a step by step process and comes with starter code for building your own chatbot. In the end we also provide some pointers for folks looking to take this proof of concept to production stage.https://www.kdnuggets.com/2017/09/meet-lucy-chatbot-prototype.html
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Machine Learning Translation and the Google Translate Algorithm
Today, we’ve decided to explore machine translators and explain how the Google Translate algorithm works.https://www.kdnuggets.com/2017/09/machine-learning-translation-google-translate-algorithm.html
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I built a chatbot in 2 hours and this is what I learned">I built a chatbot in 2 hours and this is what I learned
I set out to test two things: 1) building a bot is useless from a business perspective and 2) building bots is crazy tough. Here is what I learned.https://www.kdnuggets.com/2017/09/chatbot-2-hours-what-i-learned.html
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Putting the “Science” Back in Data Science">Putting the “Science” Back in Data Science
The scientific method to approach a problem, in my point of view, is the best way to tackle a problem and offer the best solution. If you start your data analysis by simply stating hypotheses and applying Machine Learning algorithms, this is the wrong way.https://www.kdnuggets.com/2017/09/science-data-science.html
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Search Millions of Documents for Thousands of Keywords in a Flash
We present a python library called FlashText that can search or replace keywords / synonyms in documents in O(n) – linear time.https://www.kdnuggets.com/2017/09/search-millions-documents-thousands-keywords.html
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277 Data Science Key Terms, Explained">277 Data Science Key Terms, Explained
This is a collection of 277 data science key terms, explained with a no-nonsense, concise approach. Read on to find terminology related to Big Data, machine learning, natural language processing, descriptive statistics, and much more.https://www.kdnuggets.com/2017/09/data-science-key-terms-explained.html
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First Steps of Learning Deep Learning: Image Classification in Keras
Whether you want to start learning deep learning for you career, to have a nice adventure (e.g. with detecting huggable objects) or to get insight into machines before they take over, this post is for you!https://www.kdnuggets.com/2017/08/first-steps-learning-deep-learning-image-classification-keras.html
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How I Used Deep Learning To Train A Chatbot To Talk Like Me">How I Used Deep Learning To Train A Chatbot To Talk Like Me
In this post, we’ll be looking at how we can use a deep learning model to train a chatbot on my past social media conversations in hope of getting the chatbot to respond to messages the way that I would.https://www.kdnuggets.com/2017/08/deep-learning-train-chatbot-talk-like-me.html
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5 Free Resources for Getting Started with Deep Learning for Natural Language Processing">5 Free Resources for Getting Started with Deep Learning for Natural Language Processing
This is a collection of 5 deep learning for natural language processing resources for the uninitiated, intended to open eyes to what is possible and to the current state of the art at the intersection of NLP and deep learning. It should also provide some idea of where to go next.https://www.kdnuggets.com/2017/07/5-free-resources-getting-started-deep-learning-nlp.html
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Spotlight on the Remarkable Potential of AI in KYC (Know Your Customer)
Most people would have heard of the headline-making tremendous achievements in artificial intelligence (AI): Systems defeating world champions in board games like GO and winning quiz shows. These are small realizations of AI, but there is a silent revolution taking place in other areas, including Regulatory Compliance in Financial Services.https://www.kdnuggets.com/2017/07/spotlight-remarkable-potential-ai-kyc.html
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Top 15 Python Libraries for Data Science in 2017">Top 15 Python Libraries for Data Science in 2017
Since all of the libraries are open sourced, we have added commits, contributors count and other metrics from Github, which could be served as a proxy metrics for library popularity.https://www.kdnuggets.com/2017/06/top-15-python-libraries-data-science.html
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5 Machine Learning Projects You Can No Longer Overlook, April">5 Machine Learning Projects You Can No Longer Overlook, April
It's about that time again... 5 more machine learning or machine learning-related projects you may not yet have heard of, but may want to consider checking out. Find tools for data exploration, topic modeling, high-level APIs, and feature selection herein.https://www.kdnuggets.com/2017/04/five-machine-learning-projects-cant-overlook-april.html
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Top /r/MachineLearning Posts, March: A Super Harsh Guide to Machine Learning; Is it Gaggle or Koogle?!?
A Super Harsh Guide to Machine Learning; Google is acquiring data science community Kaggle; Suggestion by Salesforce chief data scientist; Andrew Ng resigning from Baidu; Distill: An Interactive, Visual Journal for Machine Learning Researchhttps://www.kdnuggets.com/2017/04/top-reddit-machine-learning-march.html
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What is AI? Ingredients for Intelligence
This introductory overview of artificial intelligence acts as a layman's guide what AI is, and what it is made up of.https://www.kdnuggets.com/2017/04/grakn-artificial-intelligence-ingredients-intelligence.html
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Unsupervised Investments: A Comprehensive Guide to AI Investors
This article presents a list of 80 funds investing in Artificial Intelligence and Machine Learning.https://www.kdnuggets.com/2017/03/unsupervised-investments-guide-ai-investors.html
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Applying Machine Learning To March Madness
March Madness is upon us. But before you get your brackets set, check out this overview of using machine learning to do the heavy lifting for you. A great discussion, and a timely topic.https://www.kdnuggets.com/2017/03/machine-learning-march-madness.html
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Text Analytics: A Primer
Marketing scientist Kevin Gray asks Professor Bing Liu to give us a quick snapshot of text analytics in this informative interview.https://www.kdnuggets.com/2017/03/text-analytics-primer.html
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Introduction to Natural Language Processing, Part 1: Lexical Units
This series explores core concepts of natural language processing, starting with an introduction to the field and explaining how to identify lexical units as a part of data preprocessing.https://www.kdnuggets.com/2017/02/datascience-introduction-natural-language-processing-part1.html
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Deep Learning Research Review: Natural Language Processing">Deep Learning Research Review: Natural Language Processing
This edition of Deep Learning Research Review explains recent research papers in Natural Language Processing (NLP). If you don't have the time to read the top papers yourself, or need an overview of NLP with Deep Learning, this post is for you.https://www.kdnuggets.com/2017/01/deep-learning-review-natural-language-processing.html
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Artificial Intelligence and Speech Recognition for Chatbots: A Primer
Bot bots bots... Read this overview of how artificial intelligence and natural language processing are contributing to chatbot development, and where it all goes from here.https://www.kdnuggets.com/2017/01/artificial-intelligence-speech-recognition-chatbots-primer.html
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Deep Learning Can be Applied to Natural Language Processing">Deep Learning Can be Applied to Natural Language Processing
This post is a rebuttal to a recent article suggesting that neural networks cannot be applied to natural language given that language is not a produced as a result of continuous function. The post delves into some additional points on deep learning as well.https://www.kdnuggets.com/2017/01/deep-learning-applied-natural-language-processing.html
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Social Media for Marketing and Healthcare: Focus on Adverse Side Effects
Social media like twitter, facebook are very important sources of big data on the internet and using text mining, valuable insights about a product or service can be found to help marketing teams. Lets see, how healthcare companies are using big data and text mining to improve their marketing strategies.https://www.kdnuggets.com/2017/01/social-media-marketing-healthcare-focus-adverse-side-effects.html
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Academic, Research Positions in Big Data, Data Mining, Data Science, Machine Learning
To add here a short entry for an academic or research position related to AI, Big Data, Data Science, or Machine Learning, email 5 Read more »https://www.kdnuggets.com/academic/index.html
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Machine Learning & Artificial Intelligence: Main Developments in 2016 and Key Trends in 2017">Machine Learning & Artificial Intelligence: Main Developments in 2016 and Key Trends in 2017
As 2016 comes to a close and we prepare for a new year, check out the final instalment in our "Main Developments in 2016 and Key Trends in 2017" series, where experts weigh in with their opinions.https://www.kdnuggets.com/2016/12/machine-learning-artificial-intelligence-main-developments-2016-key-trends-2017.html
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Artificial Intelligence and Life in 2030
Read this engaging overview of a report from the Stanford University 100 year study of Artificial Intelligence, “a long-term investigation of the field of Artificial Intelligence (AI) and its influences on people, their communities, and society.”https://www.kdnuggets.com/2016/12/artificial-intelligence-life-2030.html
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Why Deep Learning is Radically Different From Machine Learning">Why Deep Learning is Radically Different From Machine Learning
There is a lot of confusion these days about Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL), yet the distinction is very clear to practitioners in these fields. Are you able to articulate the difference?https://www.kdnuggets.com/2016/12/deep-learning-radically-different-machine-learning.html
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Introduction to Machine Learning for Developers
Whether you are integrating a recommendation system into your app or building a chat bot, this guide will help you get started in understanding the basics of machine learning.https://www.kdnuggets.com/2016/11/intro-machine-learning-developers.html
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Questions To Ask When Moving Machine Learning From Practice to Production
An overview of applying machine learning techniques to solve problems in production. This articles covers some of the varied questions to ponder when incorporating machine learning into teams and processes.https://www.kdnuggets.com/2016/11/moving-machine-learning-practice-production.html
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An Intuitive Explanation of Convolutional Neural Networks
This article provides a easy to understand introduction to what convolutional neural networks are and how they work.https://www.kdnuggets.com/2016/11/intuitive-explanation-convolutional-neural-networks.html
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The Human Vector: Incorporate Speaker Embeddings to Make Your Bot More Powerful
One of the many ways in which bots can fail is by their (lack of) persona. Learn how speaker embeddings can help with this problem, and can help improve the persona of your bot.https://www.kdnuggets.com/2016/09/human-vector-incorporate-speaker-embedding-powerful-bot.html
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How to Become a Data Scientist – Part 1">How to Become a Data Scientist – Part 1
Check out this excellent (and exhaustive) article on becoming a data scientist, written by someone who spends their day recruiting data scientists. Do yourself a favor and read the whole way through. You won't regret it!https://www.kdnuggets.com/2016/08/become-data-scientist-part-1.html
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Multi-Task Learning in Tensorflow: Part 1
A discussion and step-by-step tutorial on how to use Tensorflow graphs for multi-task learning.https://www.kdnuggets.com/2016/07/multi-task-learning-tensorflow-part-1.html
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America’s Next Topic Model
Topic modeling is a a great way to get a bird's eye view on a large document collection using machine learning. Here are 3 ways to use open source Python tool Gensim to choose the best topic model.https://www.kdnuggets.com/2016/07/americas-next-topic-model.html
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How to Start Learning Deep Learning
Want to get started learning deep learning? Sure you do! Check out this great overview, advice, and list of resources.https://www.kdnuggets.com/2016/07/start-learning-deep-learning.html
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What Data Scientists Can Learn From Qualitative Research
Learn what data scientists can learn from qualitative researchers when it comes to analysing text, and how this relates to writing quality code.https://www.kdnuggets.com/2016/07/data-scientists-learn-from-qualitative-research.html
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Mining Twitter Data with Python Part 6: Sentiment Analysis Basics
Part 6 of this series builds on the previous installments by exploring the basics of sentiment analysis on Twitter data.https://www.kdnuggets.com/2016/07/mining-twitter-data-python-part-6.html
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Text Mining 101: Topic Modeling
We introduce the concept of topic modelling and explain two methods: Latent Dirichlet Allocation and TextRank. The techniques are ingenious in how they work – try them yourself.https://www.kdnuggets.com/2016/07/text-mining-101-topic-modeling.html
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Recursive (not Recurrent!) Neural Networks in TensorFlow
Learn how to implement recursive neural networks in TensorFlow, which can be used to learn tree-like structures, or directed acyclic graphs.https://www.kdnuggets.com/2016/06/recursive-neural-networks-tensorflow.html
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5 More Machine Learning Projects You Can No Longer Overlook
There are a lot of popular machine learning projects out there, but many more that are not. Which of these are actively developed and worth checking out? Here is an offering of 5 such projects.https://www.kdnuggets.com/2016/06/five-more-machine-learning-projects-cant-overlook.html
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Bootcamps in Analytics, Big Data, Data Science, Machine Learning
BaseCamp, an innovative data science bootcamp from Knoyd. The first cohort will start in Vienna, Austria in January 2017. Data Science Dojo, an in-person or Read more »https://www.kdnuggets.com/education/bootcamps.html
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Ethics in Machine Learning – Summary
Still worried about the AI apocalypse? Here we are discussion about the constraints and ethics for the machine learning algorithms to prevent it.https://www.kdnuggets.com/2016/06/ethics-machine-learning-mlconf.html
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The Amazing Power of Word Vectors
A fantastic overview of several now-classic papers on word2vec, the work of Mikolov et al. at Google on efficient vector representations of words, and what you can do with them.https://www.kdnuggets.com/2016/05/amazing-power-word-vectors.html
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A Data Science Approach to Writing a Good GitHub README
Readme is the first file every user will look for, whenever they are checking out the code repository. Learn, what you should write inside your readme files and analyze your existing files effectiveness.https://www.kdnuggets.com/2016/05/algorithmia-data-science-approach-good-github-readme.html
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Microsoft is Becoming M(ai)crosoft
This post is an overview and discussion of Microsoft's increasing investment in, and approach to, artificial intelligence, and how their philosophy differs from their competitors.https://www.kdnuggets.com/2016/04/microsoft-becoming-m-ai-crosoft.html
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Deep Learning for Chatbots, Part 1 – Introduction
The first in a series of tutorial posts on using Deep Learning for chatbots, this covers some of the techniques being used to build conversational agents, and goes from the current state of affairs through to what is and is not possible.https://www.kdnuggets.com/2016/04/deep-learning-chatbots-part-1.html
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Tree Kernels: Quantifying Similarity Among Tree-Structured Data
An in-depth, informative overview of tree kernels, both theoretical and practical. Includes a use case and some code after the discussion.https://www.kdnuggets.com/2016/02/tree-kernels-quantifying-similarity-tree-structured-data.html
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Elementary, My Dear Watson! An Introduction to Text Analytics via Sherlock Holmes
Want to learn about the field of text mining, go on an adventure with Sherlock & Watson. Here you will find what are different sub-domains of text mining along with a practical example.https://www.kdnuggets.com/2016/02/dato-introduction-text-analytics-sherlock-holmes.html
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AI Supercomputers: Microsoft Oxford, IBM Watson, Google DeepMind, Baidu Minwa
In the world of AI, this is the equivalent of the US and USSR competing to put their guy on the moon first. Here is a profile of some of the giants locked into the AI space race.https://www.kdnuggets.com/2016/02/ai-supercomputers-microsoft-ibm-watson-google-deepmind-baidu.html
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Top 100 Big Data Experts to Follow
Maptive gives us another list of top Big Data Influencers to check out, including data-driven reasons as to why individuals are included.https://www.kdnuggets.com/2016/01/maptive-top-big-data-experts.html
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7 Steps to Understanding Deep Learning
There are many deep learning resources freely available online, but it can be confusing knowing where to begin. Go from vague understanding of deep neural networks to knowledgeable practitioner in 7 steps!https://www.kdnuggets.com/2016/01/seven-steps-deep-learning.html
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The Art of Data Science: The Skills You Need and How to Get Them
Learn, how to turn the deluge of data into the gold by algorithms, feature engineering, reasoning out business value and ultimately building a data driven organization.https://www.kdnuggets.com/2015/12/art-data-science-skills.html
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Everything You Need to Know about Natural Language Processing
Natural language processing (NLP) helps computers understand human speech and language. We define the key NLP concepts and explain how it fits in the bigger picture of Artificial Intelligence.https://www.kdnuggets.com/2015/12/natural-language-processing-101.html
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50 Deep Learning Software Tools and Platforms, Updated
We present the popular software & toolkit resources for Deep Learning, including Caffe, Cuda-convnet, Deeplearning4j, Pylearn2, Theano, and Torch. Explore the new list!https://www.kdnuggets.com/2015/12/deep-learning-tools.html
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50 Useful Machine Learning & Prediction APIs
We present a list of 50 APIs selected from areas like machine learning, prediction, text analytics & classification, face recognition, language translation etc. Start consuming APIs!https://www.kdnuggets.com/2015/12/machine-learning-data-science-apis.html
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Deep Learning Transcends the Bag of Words
Generative RNNs are now widely popular, many modeling text at the character level and typically using unsupervised approach. Here we show how to generate contextually relevant sentences and explain recent work that does it successfully.https://www.kdnuggets.com/2015/12/deep-learning-outgrows-bag-words-recurrent-neural-networks.html
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Sentiment Analysis 101
Sentiment analysis can be incredibly useful, and can help companies better answer pertinent questions and gain valuable business insights. Sentiment analysis technologies will continue to improve as they become more widely adopted. But what can sentiment analysis do for you?https://www.kdnuggets.com/2015/12/sentiment-analysis-101.html
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Deep Learning for Visual Question Answering
Here we discuss about the Visual Question Answering problem, and I’ll also present neural network based approaches for same.https://www.kdnuggets.com/2015/11/deep-learning-visual-question-answering.html
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Why Deep Learning Works – Key Insights and Saddle Points
A quality discussion on the theoretical motivations for deep learning, including distributed representation, deep architecture, and the easily escapable saddle point.https://www.kdnuggets.com/2015/11/theoretical-deep-learning.html
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MetaMind Mastermind Richard Socher: Uncut Interview
In a wide-ranging interview, Richard Socher opens up about MetaMind, deep learning, the nature of corporate research, and the future of machine learning.https://www.kdnuggets.com/2015/10/metamind-mastermind-richard-socher-deep-learning-interview.html
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Recurrent Neural Networks Tutorial, Introduction
Recurrent Neural Networks (RNNs) are popular models that have shown great promise in NLP and many other Machine Learning tasks. Here is a much-needed guide to key RNN models and a few brilliant research papers.https://www.kdnuggets.com/2015/10/recurrent-neural-networks-tutorial.html
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SentimentBuilder: Visual Analysis of Unstructured Texts
Sankey diagrams are mainly used to visualize the flow of data on energy flows, material flow and trade-offs. SentimentBuilder found how to use them with unstructured text in their online NLP tool.https://www.kdnuggets.com/2015/09/sentimentbuilder-free-online-natural-language-processing-tool.html
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11 things to know about Sentiment Analysis
Seth Grimes, a text analytics guru, shares 11 key observations on what works, what is past, what is coming, and what to keep in mind while doing sentiment analysis.https://www.kdnuggets.com/2015/08/11-things-about-sentiment-analysis.html
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Cognitive Computing: Solving the Big Data Problem?
With a shortage of data scientists, what are the alternatives for making sense of Big Data? We examine Cognitive Computing, its strengths, and how it can fit into the current Big Data landscape.https://www.kdnuggets.com/2015/06/cognitive-computing-solving-big-data-problem.html
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Most Viewed Data Mining Videos on YouTube
The top Data Mining YouTube videos by those like Google and Revolution Analytics covers topics ranging from statistics in data mining to using R for data mining to data mining in sports.https://www.kdnuggets.com/2015/05/most-viewed-data-mining-videos-youtube.html
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WebDataCommons – the Data and Framework for Web-scale Mining
The WebDataCommons project extracts the largest publicly available hyperlink graph, large product-, address-, recipe-, and review corpora, as well as millions of HTML tables from the Common Crawl web corpus and provides the extracted data for public download.https://www.kdnuggets.com/2015/05/webdatacommons-data-web-scale-mining.html
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Algorithmia: Building a web site explorer in 5 easy steps
We show how to use Algorithmia for quickly building a functional web site explorer in 5 steps: GetLinks, PageRank, Url2text, Summarizer and AutoTag.https://www.kdnuggets.com/2015/04/algorithmia-building-web-site-explorer-5-easy-steps.html
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Deep Learning, The Curse of Dimensionality, and Autoencoders
Autoencoders are an extremely exciting new approach to unsupervised learning and for many machine learning tasks they have already surpassed the decades of progress made by researchers handpicking features.https://www.kdnuggets.com/2015/03/deep-learning-curse-dimensionality-autoencoders.html
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Machine Learning Table of Elements Decoded
Machine learning packages for Python, Java, Big Data, Lua/JS/Clojure, Scala, C/C++, CV/NLP, and R/Julia are represented using a cute but ill-fitting metaphor of a periodic table. We extract the useful links.https://www.kdnuggets.com/2015/03/machine-learning-table-elements.html
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Tinderbox: Automating Romance with Tinder and Eigenfaces
Tinderbox is a software uses machine learning and image recognition to automate Tinder, a popular app for single meetings. The author describes his experience and feedback until it started to work too well.https://www.kdnuggets.com/2015/02/tinderbox-automating-romance-tinder-eigenfaces.html
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Text Analysis 101: Document Classification
Document classification is an example of Machine Learning (ML) in the form of Natural Language Processing (NLP). By classifying text, we are aiming to assign one or more classes or categories to a document, making it easier to manage and sort.https://www.kdnuggets.com/2015/01/text-analysis-101-document-classification.html
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MetaMind Competes with IBM Watson Analytics and Microsoft Azure Machine Learning
While Microsoft and IBM rush to bring data science and visualization to the masses, MetaMind follows another path, offering deep learning as a service.https://www.kdnuggets.com/2015/01/metamind-ibm-watson-analytics-microsoft-azure-machine-learning.html
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KDnuggets™ News 14:n28, Oct 29
Features | Software | Opinions | Reports | News | Webcasts | Courses | Meetings | Jobs | Academic | Publications | Tweets | CFP Read more »https://www.kdnuggets.com/2014/n28.html
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KDnuggets™ News 14:n23, Sep 3
Features | Software | News | Opinions | Interviews | Reports | Webcasts | Courses | Meetings | Jobs | Academic | Publications | Tweets Read more »https://www.kdnuggets.com/2014/n23.html
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Interesting Social Media Datasets
Learn about some of the many interesting social media datasets available to you, some of which are quite new, and the different features and challenges they offer you for your next big data science project.https://www.kdnuggets.com/2014/08/interesting-social-media-datasets.html+
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KDnuggets™ News 14:n14, Jun 10
Features (8) | Software (3) | Opinions (14) | News (6) | Webcasts (3) | Courses (1) | Meetings and Reports (9) | Jobs (6) Read more »https://www.kdnuggets.com/2014/n14.html
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KDnuggets™ News 14:n13, May 28
Features (5) | Software (3) | Opinions (5) | News (1) | Webcasts (1) | Courses (1) | Meetings and Reports (3) | Jobs (5) Read more »https://www.kdnuggets.com/2014/n13.html
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KDnuggets™ News 14:n06, Mar 19
Features (11) | News (3) | Software (6) | Webcasts (3) | Courses (5) | Competitions (3) | Meetings (6) | Jobs (3) | Academic Read more »https://www.kdnuggets.com/2014/n06.html
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KDnuggets™ News 14:n03, Feb 5
Features (9) | Software (4) | Webcasts (2) | Courses, Events (9) | Meetings (3) | Jobs (9) | Academic (3) | Competitions (1) | Publications (7) | Tweets (7) | NewsBriefs (3) | CFP (14) | Quote Features Top Trends in Analytics and Big Data ahead of Strata 2014 Read more »https://www.kdnuggets.com/2014/n03.html
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KDnuggets™ News 14:n02, Jan 22
Features (10) | Software (3) | Webcasts (2) | Courses, Events (5) | Meetings (3) | Jobs (11) | Academic (3) | Competitions (1) | Publications Read more »https://www.kdnuggets.com/2014/n02.html
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2014 Jan Publications: Analytics, Big Data, Data Mining and Data Science
All (69) | News, Software (19) | Courses, Events (20) | Publications (15) Top KDnuggets tweets, Jan 17-19: Learning from Data: Caltech free online course; Read more »https://www.kdnuggets.com/2014/01/publications-old.html
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2014 Jan: Analytics, Big Data, Data Mining and Data Science News
All (84) | News, Software (26) | Courses, Events (30) | Publications (15) | Top Tweets (13) AltaPlana 2014 Text Analytics Market Study - Read more »https://www.kdnuggets.com/2014/01/index-old.html
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Blogs on AI, Analytics, Data Science, Machine Learning
Here are some of the most interesting and regularly-updated blogs on Analytics, Big Data, Data Science, Data Mining, and Machine Learning, in alphabetical order. Blog Read more »https://www.kdnuggets.com/websites/blogs.html