Search results for Natural Language Processing
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Top Python Libraries in 2018 in Data Science, Deep Learning, Machine Learning">Top Python Libraries in 2018 in Data Science, Deep Learning, Machine Learning
Here are the top 15 Python libraries across Data Science, Data Visualization. Deep Learning, and Machine Learning.https://www.kdnuggets.com/2018/12/top-python-libraries-2018.html
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State of Deep Learning and Major Advances: H2 2018 Review
In this post we summarise some of the key developments in deep learning in the second half of 2018, before briefly discussing the road ahead for the deep learning community.https://www.kdnuggets.com/2018/12/deep-learning-major-advances-review.html
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Solve any Image Classification Problem Quickly and Easily
This article teaches you how to use transfer learning to solve image classification problems. A practical example using Keras and its pre-trained models is given for demonstration purposes.https://www.kdnuggets.com/2018/12/solve-image-classification-problem-quickly-easily.html
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Machine Learning & AI Main Developments in 2018 and Key Trends for 2019">Machine Learning & AI Main Developments in 2018 and Key Trends for 2019
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 2018 and their 2019 key trend predictions.https://www.kdnuggets.com/2018/12/predictions-machine-learning-ai-2019.html
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Automated Web Scraping in R
How to automatically web scrape periodically so you can analyze timely/frequently updated data.https://www.kdnuggets.com/2018/12/automated-web-scraping-r.html
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A comprehensive list of Machine Learning Resources: Open Courses, Textbooks, Tutorials, Cheat Sheets and more
A thorough collection of useful resources covering statistics, classic machine learning, deep learning, probability, reinforcement learning, and more.https://www.kdnuggets.com/2018/12/finlayson-machine-learning-resources.html
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Data Science Strategy Safari: Aligning Data Science Strategy to Org Strategy
The title of this post is derived by drawing inspiration from Mintzberg’s seminal work. In this post, I am attempting to take you on a safari through the data science strategy formulation process.https://www.kdnuggets.com/2018/11/data-science-strategy-safari-aligning-data-science-strategy.html
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10 Free Must-See Courses for Machine Learning and Data Science">10 Free Must-See Courses for Machine Learning and Data Science
Check out a collection of free machine learning and data science courses to kick off your winter learning season.https://www.kdnuggets.com/2018/11/10-free-must-see-courses-machine-learning-data-science.html
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Mastering the Learning Rate to Speed Up Deep Learning
Figuring out the optimal set of hyperparameters can be one of the most time consuming portions of creating a machine learning model, and that’s particularly true in deep learning.https://www.kdnuggets.com/2018/11/mastering-learning-rate-speed-up-deep-learning.html
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The Most in Demand Skills for Data Scientists">The Most in Demand Skills for Data Scientists
Data scientists are expected to know a lot — machine learning, computer science, statistics, mathematics, data visualization, communication, and deep learning. How should data scientists who want to be in demand by employers spend their learning budget?https://www.kdnuggets.com/2018/11/most-demand-skills-data-scientists.html
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Named Entity Recognition and Classification with Scikit-Learn">Named Entity Recognition and Classification with Scikit-Learn
Named Entity Recognition and Classification is a process of recognizing information units like names, including person, organization and location names, and numeric expressions from unstructured text. The goal is to develop practical and domain-independent techniques in order to detect named entities with high accuracy automatically.https://www.kdnuggets.com/2018/10/named-entity-recognition-classification-scikit-learn.html
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Machine Reading Comprehension: Learning to Ask & Answer
Investigating the dual ask-answer network, covering the embedding, encoding, attention and output layer, as well as the loss function, with code examples to help you get started.https://www.kdnuggets.com/2018/10/machine-reading-comprehension-learning-ask-answer.html
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Building a Machine Learning Model through Trial and Error
A step-by-step guide that includes suggestions on how to preprocess data and deriving features from this. This article also contains links to help you explore additional resources about machine learning methods and other examples.https://www.kdnuggets.com/2018/09/mathworks-building-machine-learning-model-through-trial-error.html
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Data Capture – the Deep Learning Way
An overview of how an information extraction pipeline built from scratch on top of deep learning inspired by computer vision can shakeup the established field of OCR and data capture.https://www.kdnuggets.com/2018/09/data-capture-deep-learning-way.html
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Machine Learning for Text Classification Using SpaCy in Python
In this post, we will demonstrate how text classification can be implemented using spaCy without having any deep learning experience.https://www.kdnuggets.com/2018/09/machine-learning-text-classification-using-spacy-python.html
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AI Knowledge Map: How To Classify AI Technologies">AI Knowledge Map: How To Classify AI Technologies
What follows is then an effort to draw an architecture to access knowledge on AI and follow emergent dynamics, a gateway of pre-existing knowledge on the topic that will allow you to scout around for additional information and eventually create new knowledge on AI.https://www.kdnuggets.com/2018/08/ai-knowledge-map-classify-ai-technologies.html
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Topic Modeling with LSA, PLSA, LDA & lda2Vec">Topic Modeling with LSA, PLSA, LDA & lda2Vec
This article is a comprehensive overview of Topic Modeling and its associated techniques.https://www.kdnuggets.com/2018/08/topic-modeling-lsa-plsa-lda-lda2vec.html
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Multi-Class Text Classification with Scikit-Learn
The vast majority of text classification articles and tutorials on the internet are binary text classification such as email spam filtering and sentiment analysis. Real world problem are much more complicated than that.https://www.kdnuggets.com/2018/08/multi-class-text-classification-scikit-learn.html
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Affordable online news archives for academic research
Many researchers need access to multi-year historical repositories of online news articles. We identified three companies that make such access affordable, and spoke with their CEOs.https://www.kdnuggets.com/2018/08/affordable-online-news-archives.html
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Data Retrieval with Web Scraping: A Practitioner’s Guide to NLP
Proven and tested hands-on strategies to tackle NLP tasks.https://www.kdnuggets.com/2018/07/practitioners-guide-processing-understanding-text-1.html
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9 Reasons why your machine learning project will fail
This article explains in detail some of the issues that you may face during your machine learning project.https://www.kdnuggets.com/2018/07/why-machine-learning-project-fail.html
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Text Mining on the Command Line">Text Mining on the Command Line
In this tutorial, I use raw bash commands and regex to process raw and messy JSON file and raw HTML page. The tutorial helps us understand the text processing mechanism under the hood.https://www.kdnuggets.com/2018/07/text-mining-command-line.html
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Text Classification & Embeddings Visualization Using LSTMs, CNNs, and Pre-trained Word Vectors
In this tutorial, I classify Yelp round-10 review datasets. After processing the review comments, I trained three model in three different ways and obtained three word embeddings.https://www.kdnuggets.com/2018/07/text-classification-lstm-cnn-pre-trained-word-vectors.html
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Top 20 Python Libraries for Data Science in 2018">Top 20 Python Libraries for Data Science in 2018
Our selection actually contains more than 20 libraries, as some of them are alternatives to each other and solve the same problem. Therefore we have grouped them as it's difficult to distinguish one particular leader at the moment.https://www.kdnuggets.com/2018/06/top-20-python-libraries-data-science-2018.html
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30 Free Resources for Machine Learning, Deep Learning, NLP & AI">30 Free Resources for Machine Learning, Deep Learning, NLP & AI
Check out this collection of 30 ML, DL, NLP & AI resources for beginners, starting from zero and slowly progressing to the point that readers should have an idea of where to go next.https://www.kdnuggets.com/2018/06/30-free-resources-machine-learning-deep-learning-nlp-ai.html
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Detecting Sarcasm with Deep Convolutional Neural Networks">Detecting Sarcasm with Deep Convolutional Neural Networks
Detection of sarcasm is important in other areas such as affective computing and sentiment analysis because such expressions can flip the polarity of a sentence.https://www.kdnuggets.com/2018/06/detecting-sarcasm-deep-convolutional-neural-networks.html
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Generating Text with RNNs in 4 Lines of Code">Generating Text with RNNs in 4 Lines of Code
Want to generate text with little trouble, and without building and tuning a neural network yourself? Let's check out a project which allows you to "easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code."https://www.kdnuggets.com/2018/06/generating-text-rnn-4-lines-code.html
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Advice For Applying To Data Science Jobs
A comprehensive guide to applying for a job in data science, covering the application, interview and offer stage.https://www.kdnuggets.com/2018/06/advice-applying-data-science-jobs.html
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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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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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9 Must-have skills you need to become a Data Scientist, updated">9 Must-have skills you need to become a Data Scientist, updated
Check out this collection of 9 (plus some additional freebies) must-have skills for becoming a data scientist.https://www.kdnuggets.com/2018/05/simplilearn-9-must-have-skills-data-scientist.html
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An Introduction to Deep Learning for Tabular Data
This post will discuss a technique that many people don’t even realize is possible: the use of deep learning for tabular data, and in particular, the creation of embeddings for categorical variables.https://www.kdnuggets.com/2018/05/introduction-deep-learning-tabular-data.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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GANs in TensorFlow from the Command Line: Creating Your First GitHub Project
In this article I will present the steps to create your first GitHub Project. I will use as an example Generative Adversarial Networks.https://www.kdnuggets.com/2018/05/zimbres-first-github-project-gans.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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Top 7 Data Science Use Cases in Finance
We have prepared a list of data science use cases that have the highest impact on the finance sector. They cover very diverse business aspects from data management to trading strategies, but the common thing for them is the huge prospects to enhance financial solutions.https://www.kdnuggets.com/2018/05/top-7-data-science-use-cases-finance.html
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Data Augmentation: How to use Deep Learning when you have Limited Data
This article is a comprehensive review of Data Augmentation techniques for Deep Learning, specific to images.https://www.kdnuggets.com/2018/05/data-augmentation-deep-learning-limited-data.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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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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How to Make AI More Accessible
I recently was a guest speaker at the Stanford AI Salon on the topic of accessiblity in AI, which included a free-ranging discussion among assembled members of the Stanford AI Lab. There were a number of interesting questions and topics, so I thought I would share a few of my answers here.https://www.kdnuggets.com/2018/04/make-ai-more-accessible.html
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The Dirty Little Secret Every Data Scientist Knows (but won’t admit)
Most people don’t realize, but the actual “fancy” machine learning algorithm is like the last mile of the marathon. There is so much that must be done before you get there!https://www.kdnuggets.com/2018/04/dirty-little-secret-data-scientist.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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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 20 Deep Learning Papers, 2018 Edition">Top 20 Deep Learning Papers, 2018 Edition
Deep Learning is constantly evolving at a fast pace. New techniques, tools and implementations are changing the field of Machine Learning and bringing excellent results.https://www.kdnuggets.com/2018/03/top-20-deep-learning-papers-2018.html
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Semantic Segmentation Models for Autonomous Vehicles
State-of-the-art Semantic Segmentation models need to be tuned for efficient memory consumption and fps output to be used in time-sensitive domains like autonomous vehicles.https://www.kdnuggets.com/2018/03/semantic-segmentation-models-autonomous-vehicles.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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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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How StockTwits Applies Social and Sentiment Data Science
StockTwits is a social network for investors and traders, giving them a platform to share assertions and perceptions, analyses and predictions.https://www.kdnuggets.com/2018/03/stocktwits-social-sentiment-data-science.html
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Data Science in Fashion">Data Science in Fashion
Fashion industry is an extremely competitive and dynamic market. Trends and styles change with the blink of an eye. Data Science can be used here on historical data to predict the trends which will be “Hot” hence potentially saving a lot of time and money.https://www.kdnuggets.com/2018/03/data-science-fashion.html
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Where AI is already rivaling humans
Since 2011, AI hit hypergrowth, and researchers have created several AI solutions that are almost as good as – or better than – humans in several domains, including games, healthcare, computer vision and object recognition, speech to text conversion, speaker recognition, and improved robots and chat-bots for solving specific problems.https://www.kdnuggets.com/2018/02/domains-ai-rivaling-humans.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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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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A Simple Starter Guide to Build a Neural Network">A Simple Starter Guide to Build a Neural Network
This guide serves as a basic hands-on work to lead you through building a neural network from scratch. Most of the mathematical concepts and scientific decisions are left out.https://www.kdnuggets.com/2018/02/simple-starter-guide-build-neural-network.html
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The 8 Neural Network Architectures Machine Learning Researchers Need to Learn">The 8 Neural Network Architectures Machine Learning Researchers Need to Learn
In this blog post, I want to share the 8 neural network architectures from the course that I believe any machine learning researchers should be familiar with to advance their work.https://www.kdnuggets.com/2018/02/8-neural-network-architectures-machine-learning-researchers-need-learn.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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Top Stories of 2017: 10 Free Must-Read Books for Machine Learning and Data Science; Python overtakes R, becomes the leader in Data Science, Machine Learning platforms
Also Top 10 Machine Learning Algorithms for Beginners; 30 Essential Data Science, Machine Learning & Deep Learning Cheat Sheets.https://www.kdnuggets.com/2017/12/top-stories-2017.html
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The 10 Deep Learning Methods AI Practitioners Need to Apply
Deep learning emerged from that decade’s explosive computational growth as a serious contender in the field, winning many important machine learning competitions. The interest has not cooled as of 2017; today, we see deep learning mentioned in every corner of machine learning.https://www.kdnuggets.com/2017/12/10-deep-learning-methods-ai-practitioners-need-apply.html
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Data Science, Machine Learning: Main Developments in 2017 and Key Trends in 2018">Data Science, Machine Learning: Main Developments in 2017 and Key Trends in 2018
The leading experts in the field on the main Data Science, Machine Learning, Predictive Analytics developments in 2017 and key trends in 2018.https://www.kdnuggets.com/2017/12/data-science-machine-learning-main-developments-trends.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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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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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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Best Masters in Data Science and Analytics in US/Canada
Second comprehensive list of master's degrees in the US and Canada with tuition information and duration.https://www.kdnuggets.com/2017/11/best-masters-data-science-analytics-us-canada.html
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TensorFlow: What Parameters to Optimize?
Learning TensorFlow Core API, which is the lowest level API in TensorFlow, is a very good step for starting learning TensorFlow because it let you understand the kernel of the library. Here is a very simple example of TensorFlow Core API in which we create and train a linear regression model.https://www.kdnuggets.com/2017/11/tensorflow-parameters-optimize.html
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Want to know how Deep Learning works? Here’s a quick guide for everyone">Want to know how Deep Learning works? Here’s a quick guide for everyone
Once you’ve read this article, you will understand the basics of AI and ML. More importantly, you will understand how Deep Learning, the most popular type of ML, works.https://www.kdnuggets.com/2017/11/deep-learning-works-quick-guide-everyone.html
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Getting Started with Machine Learning in One Hour!
Here is a machine learning getting started guide which grew out of the author's notes for a one hour talk on the subject. Hopefully you find the path helpful.https://www.kdnuggets.com/2017/11/getting-started-machine-learning-one-hour.html
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TensorFlow: Building Feed-Forward Neural Networks Step-by-Step">TensorFlow: Building Feed-Forward Neural Networks Step-by-Step
This article will take you through all steps required to build a simple feed-forward neural network in TensorFlow by explaining each step in details.https://www.kdnuggets.com/2017/10/tensorflow-building-feed-forward-neural-networks-step-by-step.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 Bootcamp in Zurich, Switzerland, January 15 – April 6, 2018
Come to the land of chocolate and Data Science where the local tech scene is booming and the jobs are a plenty. Learn the most important concepts from top instructors by doing and through projects. Use code KDNUGGETS to save.https://www.kdnuggets.com/2017/10/propulsion-data-science-bootcamp-zurich.html
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How I started with learning AI in the last 2 months">How I started with learning AI in the last 2 months
The relevance of a full stack developer will not be enough in the changing scenario of things. In the next two years, full stack will not be full stack without AI skills.https://www.kdnuggets.com/2017/10/how-started-learning-ai.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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An Intuitive Guide to Deep Network Architectures
How and why do different Deep Learning models work? We provide an intuitive explanation for 3 very popular DL models: Resnet, Inception, and Xception.https://www.kdnuggets.com/2017/08/intuitive-guide-deep-network-architectures.html
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Introduction to Neural Networks, Advantages and Applications">Introduction to Neural Networks, Advantages and Applications
Artificial Neural Network (ANN) algorithm mimic the human brain to process information. Here we explain how human brain and ANN works.https://www.kdnuggets.com/2017/07/introduction-neural-networks-advantages-applications.html
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6 Reasons Why Python Is Suddenly Super Popular">6 Reasons Why Python Is Suddenly Super Popular
Python is a general-purpose language — sometimes referred to as utilitarian — which is designed to be simple to read and write. The point that it’s not a complex language is important.
https://www.kdnuggets.com/2017/07/6-reasons-python-suddenly-super-popular.html
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The Strange Loop in Deep Learning
This ‘strange loop’ is in fact is the fundamental reason for what Yann LeCun describes as “the coolest idea in machine learning in the last twenty years.”https://www.kdnuggets.com/2017/07/strange-loop-deep-learning.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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Does Machine Learning Have a Future Role in Cyber Security?
In the past, ML learning hasn't had as much success in cyber security as in other fields. Many early attempts struggled with problems such as generating too many false positives, which resulted mixed attitudes towards it.https://www.kdnuggets.com/2017/06/machine-learning-future-role-cyber-security.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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The Two Phases of Gradient Descent in Deep Learning
In short, you reach different resting placing with different SGD algorithms. That is, different SGDs just give you differing convergence rates due to different strategies, but we do expect that they all end up at the same results!https://www.kdnuggets.com/2017/05/two-phases-gradient-descent-deep-learning.html
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Deep Learning – Past, Present, and Future">Deep Learning – Past, Present, and Future
There is a lot of buzz around deep learning technology. First developed in the 1940s, deep learning was meant to simulate neural networks found in brains, but in the last decade 3 key developments have unleashed its potential.https://www.kdnuggets.com/2017/05/deep-learning-big-deal.html
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The Analytics of Emotion and Depression
Analytics can be used to provide a boost to the cure of depression. How analytics is being adopted by companies like Microsoft, Facebook to handle and detect vulnerable targets of depression.https://www.kdnuggets.com/2017/04/analytics-emotion-depression.html
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The Data Science of Steel, or Data Factory to Help Steel Factory
Applying Machine Learning to steel production is really hard! Here are some lessons from Yandex researchers on how to balance the need for findings to be accurate, useful, and understandable at the same time.https://www.kdnuggets.com/2017/04/yandex-data-science-steel.html
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Awesome Deep Learning: Most Cited Deep Learning Papers">Awesome Deep Learning: Most Cited Deep Learning Papers
This post introduces a curated list of the most cited deep learning papers (since 2012), provides the inclusion criteria, shares a few entry examples, and points to the full listing for those interested in investigating further.https://www.kdnuggets.com/2017/04/awesome-deep-learning-most-cited-papers.html
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The dynamics between AI and IoT
We see the need for a new type of Engineer who will combine knowledge from Electronics & IoT with Machine learning, AI, Robotics, Cloud and Data management (devops).https://www.kdnuggets.com/2017/04/dynamics-ai-iot.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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Putting Together A Full-Blooded AI Maturity Model
Here is a proposed “7A” model that is useful enough to capture of the core of what AI offers without falsely implying there is a static body of best practices in this area.https://www.kdnuggets.com/2017/04/ai-maturity-model.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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A Beginner’s Guide to Tweet Analytics with Pandas
Unlike a lot of other tutorials which often pull from the real-time Twitter API, we will be using the downloadable Twitter Analytics data, and most of what we do will be done in Pandas.https://www.kdnuggets.com/2017/03/beginners-guide-tweet-analytics-pandas.html
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Getting Started with Deep Learning
This post approaches getting started with deep learning from a framework perspective. Gain a quick overview and comparison of available tools for implementing neural networks to help choose what's right for you.https://www.kdnuggets.com/2017/03/getting-started-deep-learning.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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Working With Numpy Matrices: A Handy First Reference
This introductory tutorial does a great job of outlining the most common Numpy array creation and manipulation functionality. A good post to keep handy while taking your first steps in Numpy, or to use as a handy reminder.https://www.kdnuggets.com/2017/03/working-numpy-matrices.html
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The Data Science Puzzle, Revisited
The data science puzzle is re-examined through the relationship between several key concepts in the realm, and incorporates important updates and observations from the past year. The result is a modified explanatory graphic and rationale.https://www.kdnuggets.com/2017/01/data-science-puzzle-revisited.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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Top 20 Python Machine Learning Open Source Projects, updated">Top 20 Python Machine Learning Open Source Projects, updated
Open Source is the heart of innovation and rapid evolution of technologies, these days. This article presents you Top 20 Python Machine Learning Open Source Projects of 2016 along with very interesting insights and trends found during the analysis.https://www.kdnuggets.com/2016/11/top-20-python-machine-learning-open-source-updated.html
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Data Science and Big Data, Explained">Data Science and Big Data, Explained
This article is meant to give the non-data scientist a solid overview of the many concepts and terms behind data science and big data. While related terms will be mentioned at a very high level, the reader is encouraged to explore the references and other resources for additional detail.https://www.kdnuggets.com/2016/11/big-data-data-science-explained.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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How to Rank 10% in Your First Kaggle Competition
This post presents a pathway to achieving success in Kaggle competitions as a beginner. The path generalizes beyond competitions, however. Read on for insight into succeeding while approaching any data science project.https://www.kdnuggets.com/2016/11/rank-ten-precent-first-kaggle-competition.html
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Introduction to Trainspotting: Computer Vision, Caltrain, and Predictive Analytics
We previously analyzed delays using Caltrain’s real-time API to improve arrival predictions, and we have modeled the sounds of passing trains to tell them apart. In this post we’ll start looking at the nuts and bolts of making our Caltrain work possible.https://www.kdnuggets.com/2016/11/introduction-trainspotting.html
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9 Key Deep Learning Papers, Explained">9 Key Deep Learning Papers, Explained
If you are interested in understanding the current state of deep learning, this post outlines and thoroughly summarizes 9 of the most influential contemporary papers in the field.https://www.kdnuggets.com/2016/09/9-key-deep-learning-papers-explained.html
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How Convolutional Neural Networks Work
Get an overview of what is going on inside convolutional neural networks, and what it is that makes them so effective.https://www.kdnuggets.com/2016/08/brohrer-convolutional-neural-networks-explanation.html
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Introduction to Local Interpretable Model-Agnostic Explanations (LIME)
Learn about LIME, a technique to explain the predictions of any machine learning classifier.https://www.kdnuggets.com/2016/08/introduction-local-interpretable-model-agnostic-explanations-lime.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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Top Machine Learning MOOCs and Online Lectures: A Comprehensive Survey
This post reviews Machine Learning MOOCs and online lectures for both the novice and expert audience.https://www.kdnuggets.com/2016/07/top-machine-learning-moocs-online-lectures.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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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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Subscribe to KDnuggets News
Get the FREE ebook 'The Great Big Natural Language Processing Primer' and 'The Complete Collection of Data Science Cheat Sheets' along with the leading newsletter Read more »https://www.kdnuggets.com/news/subscribe.html
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Machine Learning Trends and the Future of Artificial Intelligence
The confluence of data flywheels, the algorithm economy, and cloud-hosted intelligence means every company can now be a data company, every company can now access algorithmic intelligence, and every app can now be an intelligent app.https://www.kdnuggets.com/2016/06/machine-learning-trends-future-ai.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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When Does Deep Learning Work Better Than SVMs or Random Forests®?">When Does Deep Learning Work Better Than SVMs or Random Forests®?
Some advice on when a deep neural network may or may not outperform Support Vector Machines or Random Forests.https://www.kdnuggets.com/2016/04/deep-learning-vs-svm-random-forest.html
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Top 15 Frameworks for Machine Learning Experts
Either you are a researcher, start-up or big organization who wants to use machine learning, you will need the right tools to make it happen. Here is a list of the most popular frameworks for machine learning.https://www.kdnuggets.com/2016/04/top-15-frameworks-machine-learning-experts.html
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The Data Science Puzzle, Explained
The puzzle of data science is examined through the relationship between several key concepts in the data science realm. As we will see, far from being concrete concepts etched in stone, divergent opinions are inevitable; this is but another opinion to consider.https://www.kdnuggets.com/2016/03/data-science-puzzle-explained.html
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The Data Science Process, Rediscovered
The Data Science Process is a relatively new framework for doing data science. It is compared to previous similar frameworks, and a discussion on process innovation versus repetition is then undertaken.https://www.kdnuggets.com/2016/03/data-science-process-rediscovered.html
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Data Science and Disability
Data Science and Artificial Intelligence has come to the forefront of technology in the last few years. Learn, how practitioners are taking a more philanthropic outlook on life, supporting people suffering with both physical and mental disabilities.https://www.kdnuggets.com/2016/03/data-science-disability.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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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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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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Software development skills for data scientists
Data science is not only about building the models and sharing insights, many times they have to collaborate in deploying models and sharing them with software developers, learn which things to keep in mind while doing so.https://www.kdnuggets.com/2015/12/software-development-skills-data-scientists.html