2017 Jul
All (100) | Courses, Education (4) | Meetings (15) | News, Features (16) | Opinions, Interviews (26) | Software (2) | Tutorials, Overviews (30) | Webcasts & Webinars (7)
- Artificial Intelligence Conference – Exclusive KDnuggets Offer - Jul 31, 2017.
The O'Reilly AI Conference comes to San Francisco Sept 17-20. Early Price ends August 4, and space is limited. Save an extra 20% on most passes with KDnuggets exclusive code PCKDNG.
- Digital Transformation through Data Democratization - Jul 31, 2017.
Digital innovators will succeed because enterprise data doesn’t belong to silos and data has immense value, but only if available as a “whole”, to allow full picture of the enterprise rather than short term trends or baseline BI reports.
- Top Stories, Jul 24-30: When not to use Deep Learning; 6 Reasons Why Python Is Suddenly Super Popular - Jul 31, 2017.
Also: Machine Learning Exercises in Python: An Introductory Tutorial Series; Introduction to Neural Networks, Advantages and Applications; The Internet of Things: An Introductory Tutorial Series; The BI & Data Analysis Conundrum: 8 Reasons Why Many Big Data Analytics Solutions Fail to Deliver Value
- The Key to Data Monetization - Jul 31, 2017.
While I have talked frequently about the concept of Analytic Profiles, I’ve never written a blog that details how Analytic Profiles work. So let’s create a “Day in the Life” of an Analytic Profile to explain how an Analytic Profile works to capture and “monetize” your analytic assets.
- Predictive Data Science in R, Santa Clara, Sep 16 - Jul 28, 2017.
The class lectures include best practices of setting up a data mining project and preprocessing, going through a first sprint in R, using RStudio and packages like data.table, xgboost, trees and neural nets and caret.
- DataRobot: Become a Data Science Superhero – Watch on Demand - Jul 28, 2017.
A demo of DataRobot will show you how to transform your predictive analytics team into a League of Superheroes, cranking out predictive models at the speed of thought!
- When Data Science Is Not Enough: Deriving Signal from Maritime Observations - Jul 28, 2017.
We examine the limits of "data science-first" thinking - letting technical skills drive the analysis, and only later adding domain understanding.
- The Internet of Things: An Introductory Tutorial Series - Jul 28, 2017.
In this series of post, the author will be presenting a set of Internet of Things technologies and applications in the form of tutorial in chapter form. Basic concepts are covered with an approachable style, not heaped in technical terms.
- TDWI Big Data and Analytics for Business Advantage – Exclusive, Complimentary Summit – Apply by Aug 11 - Jul 27, 2017.
Learn to use analytics to deploy innovative business solutions at TDWI Big Data and Analytics for Business Advantage Summit, Oct 8-10 in Savannah, GA. Apply for this exclusive, complimentary event by Aug 11.
- How to squeeze the most from your training data - Jul 27, 2017.
In many cases, getting enough well-labelled training data is a huge hurdle for developing accurate prediction systems. Here is an innovative approach which uses SVM to get the most from training data.
- The Machine Learning Abstracts: Classification - Jul 27, 2017.
Classification is the process of categorizing or “classifying” some items into a predefined set of categories or “classes”. It is exactly the same even when a machine does so. Let’s dive a little deeper.
- Machine Learning and Misinformation - Jul 27, 2017.
The creative aspects of machine learning are overshadowed by visions of an autonomous future, but machine learning is a powerful tool for communication. Most machine learning in today’s products is related to understanding.
- Top KDnuggets tweets, Jul 19-25: 5 Free Resources for Getting Started with #DeepLearning for NLP; 10 Free Must-Read Books for ML, DS - Jul 26, 2017.
Also: 10 Free Must-Read Books for #MachineLearning and #DataScience; 4 cases when not to use #DeepLearning; #Internet speed and cost by country
- The Marketing Metrics and Analytics Summit, Chicago, Sep 26-27 - Jul 26, 2017.
The summit will provide you with all the practical know-how you need to take your organization's marketing measurement game to the next level.
- KDnuggets Free Pass to The AI Conference, San Francisco, Sep 17-20 - Jul 26, 2017.
AI is the hottest technology now. You can win a free pass to the new AI conference in SF in September or use code PCKDNG to save right now.
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The BI & Data Analysis Conundrum: 8 Reasons Why Many Big Data Analytics Solutions Fail to Deliver Value - Jul 26, 2017.
Why many BI & Analytics projects/solutions fail to deliver the business value? Let’s find out the answers to such questions. - Machine Learning Exercises in Python: An Introductory Tutorial Series - Jul 26, 2017.
This post presents a summary of a series of tutorials covering the exercises from Andrew Ng's machine learning class on Coursera. Instead of implementing the exercises in Octave, the author has opted to do so in Python, and provide commentary along the way.
- Learn from DeepMind at Deep Learning, AI Assistant Summits London, Sep 21-22 - Jul 25, 2017.
We’d like to update you on RE•WORK’s Deep Learning Global Summit Series and the upcoming summits in London this September. We have an exclusive code to give KDnuggets readers discounted tickets to these events as well as on-demand content and expert interviews.
- SIGKDD Elects Jian Pei as Chair, Michael Zeller Treasurer, New Executive Committee - Jul 25, 2017.
New SIGKDD chair will be Dr. Jian Pei. He says SIGKDD must continue serving academia and industry in a balanced and innovative manner.
- Introduction to Neural Networks, Advantages and Applications - Jul 25, 2017.
Artificial Neural Network (ANN) algorithm mimic the human brain to process information. Here we explain how human brain and ANN works.
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6 Reasons Why Python Is Suddenly Super Popular - Jul 25, 2017.
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.
- The Truth About Bayesian Priors and Overfitting - Jul 25, 2017.
Many of the considerations we will run through will be directly applicable to your everyday life of applying Bayesian methods to your specific domain.
- Revolutionizing Data Science Package Management, July 25 - Jul 24, 2017.
Learn how Anaconda solves one of the most headache-inducing problems in data science—overcoming the package dependency nightmare—through the power of conda, in this webinar, on July 25.
- Predictive Analytics World, London, 11-12 October – Agenda is Live - Jul 24, 2017.
The agenda for PAW London 2017 has just been released and we want you to be among the first to know what the hot topics will be this year.
- Summary of Unintuitive Properties of Neural Networks - Jul 24, 2017.
Neural networks work really well on many problems, including language, image and speech recognition. However understanding how they work is not simple, and here is a summary of unusual and counter intuitive properties they have.
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When not to use deep learning - Jul 24, 2017.
Despite DL many successes, there are at least 4 situations where it is more of a hindrance, including low-budget problems, or when explaining models and features to general public is required.
- Top Stories, Jul 17-23: Machine Learning Applied to Big Data, Explained; 5 Free Resources for Getting Started with Deep Learning for Natural Language Processing - Jul 24, 2017.
Also: How GDPR Affects Data Science,AI and Deep Learning, Explained Simply; Are Most Machine Learning Experts Turning to Deep Learning?; Design by Evolution: How to evolve your neural network with AutoML
- Top Quora Data Science Writers and Their Best Advice, Updated - Jul 24, 2017.
Get some insight into tips and tricks, the future of the field, career advice, code snippets, and more from the top data science writers on Quora.
- Optimism about AI improving society is high, but drops with experience developing AI systems - Jul 21, 2017.
While about 60% of KDnuggets readers think AI and Automation will improve society, the optimism drops significantly among those with 4 or more years experience developing AI systems. Should we pay more attention to the experts?
- Take The Next Step In Your Data Science Career - Jul 21, 2017.
The Saint Mary's College Master of Science in Data Science program will prepare you to enter into the data analysis process at any stage, from the initial formulation of the question, to visualizing data, to interpreting the results and drawing conclusions.
- AI and Deep Learning, Explained Simply - Jul 21, 2017.
AI can now see, hear, and even bluff better than most people. We look into what is new and real about AI and Deep Learning, and what is hype or misinformation.
- Intelligence and Cognition: I Do Not Think They Mean What You Think They Mean - Jul 21, 2017.
You have likely noticed the recent relative uptick in the use of the words "intelligence" and "cognitive," as well as their derivatives. Are such terms really true or are they a marketing device?
- Picking an Optimizer for Style Transfer - Jul 21, 2017.
Gradient Descent, Adam or Limited-memory Broyden–Fletcher–Goldfarb–Shanno? Which will optimize your style transfer neural network faster and better? Read this post for a data-backed discussion.
- Big Data Innovation, Data Visualization Summits, Boston, Sep 7-8 - Jul 20, 2017.
Visualize your data, Demonstrate its value, and tailor your pitch - learn how from the industry leaders in Boston.
- Deep Learning, AI Assistant Summits London feature DeepMind and much more, Sep 21-22 – KDnuggets Offer - Jul 20, 2017.
The Deep Learning Summit London and the AI Assistant Summit London will be continuing the RE•WORK Global Summit Series this September 21 & 22. Early Bird discount is ending on July 28th. Register now to guarantee a spot at the Summit and use the discount code KDNUGGETS to save 20% on all tickets.
- IEEE ICDM 2017 Call For Award Nominations, due Aug 15 - Jul 20, 2017.
Nominations sought for outstanding research and service contributions in the field of data mining and data science.
- Emotional Intelligence for Data Science Teams - Jul 20, 2017.
Here are three lessons for making and demonstrating a greater business impact to your organization, according to Domino Labs most successful customers.
- Design by Evolution: How to evolve your neural network with AutoML - Jul 20, 2017.
The gist ( tl;dr): Time to evolve! I’m gonna give a basic example (in PyTorch) of using evolutionary algorithms to tune the hyper-parameters of a DNN.
- Populating a GRAKN.AI Knowledge Graph with the World - Jul 20, 2017.
This updated article describes how to move SQL data into a GRAKN.AI knowledge graph.
- Top KDnuggets tweets, Jul 12-18: 10 Free #MustRead Books for #MachineLearning and #DataScience; Why #AI and Machine Learning? - Jul 19, 2017.
Also top 32 Reasons #DataScience Projects and Teams Fail; Text Classifier Algorithms in #MachineLearning; The 4 Types of #Data #Analytics: Descriptive, Diagnostic ...
- PAW Keynotes: Tips, Tricks, Mistakes, and Examples - Jul 19, 2017.
PAW Business, Oct 29 - Nov 2, 2017 in NYC, will be packed with the top machine learning and predictive analytics experts, practitioners, authors, business thought leaders - check the keynotes.
- Hacking in silico protein engineering with Machine Learning and AI, explained - Jul 19, 2017.
Proteins are building blocks of all living matter. Although tremendous progress has been made, protein engineering remains laborious, expensive and truly complicated. Here is how Machine Learning can help.
- Road Lane Line Detection using Computer Vision models - Jul 19, 2017.
A tutorial on how to implement a computer vision data pipeline for road lane detection used by self-driving cars.
- 5 Free Resources for Getting Started with Deep Learning for Natural Language Processing - Jul 19, 2017.
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.
- Free Guidebook: Build a Complete Predictive Maintenance Strategy - Jul 18, 2017.
Learn how predictive maintenance differs from and better than traditional one; Use cases and potential data sources; and next steps for getting started.
- Top Modules and Features of Business Intelligence Tools - Jul 18, 2017.
What makes BI tools great? What features are important while selecting a good BI tool? Let’s have a look.
- Artificial Intuition – A Breakthrough Cognitive Paradigm - Jul 18, 2017.
This article is just a reflection of my current understanding of the language of Deep Learning Meta Meta-Model. That’s definitely a mouth full, so to make life simpler for everyone, I just call this the Deep Learning Canonical Patterns.
- Are Most Machine Learning Experts Turning to Deep Learning? - Jul 18, 2017.
Read a short opinion on what the impact of machine learning researchers focusing on deep learning will be.
- Top Stories, Jul 10-16: The 4 Types of Data Analytics; What Are Artificial Intelligence, Machine Learning, and Deep Learning? - Jul 17, 2017.
Also: The Strange Loop in Deep Learning; How to Build a Data Science Pipeline; Automated Machine Learning - A Paradigm Shift That Accelerates Data Scientist Productivity; Medical Image Analysis with Deep Learning, Part 4
- Author of “Everybody Lies” to Speak at Predictive Analytics World NYC - Jul 17, 2017.
The author of "Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us ..." will be featured speaker at PAW NYC, Oct 29 - Nov 2. KDnuggets readers get special discount.
- How GDPR Affects Data Science - Jul 17, 2017.
Coming European GDPR directive affects data science practice mainly in 3 areas: limits on data processing and consumer profiling, a “right to an explanation” for automated decision-making, and accountability for bias and discrimination in automated decisions.
- Optimizing Web sites: Advances thanks to Machine Learning - Jul 17, 2017.
Machine learning has revitalized a nearly dormant method, leading to a powerful approach for optimizing Web pages, finding the best of thousands of alternatives.
- Machine Learning Applied to Big Data, Explained - Jul 17, 2017.
Machine learning with Big Data is, in many ways, different than "regular" machine learning. This informative image is helpful in identifying the steps in machine learning with Big Data, and how they fit together into a process of their own.
- Cartoon: The First Ever Self-Driving, Deep Learning Grill - Jul 15, 2017.
New KDnuggets Cartoon looks at what happens when self-driving craze collides with the traditional summer pastime of grilling.
- Strategic Analytics Summit, Las Vegas, Sep 13-14 – KDnuggets Offer - Jul 14, 2017.
This Summit will bring together Big Data thought leaders, top business executives and analytics experts for two days of insights, learning and networking. Use code KDNU17 for 25% off.
- DataRobot: Become a Data Science SuperHero, Webinar, July 25 - Jul 14, 2017.
DataRobot machine learning automation platform transforms you from mild-mannered to superhuman in your abilities to develop and deploy highly-accurate predictive models. Learn more in this webinar.
- How to Turn your Data Science Projects into a Success - Jul 14, 2017.
This interview with Dr. Olav Laudy, Chief Data Scientist for IBM Analytics, is a summary of a recent conference where he participated in a panel on the Big Data and Analytics
- How to Build a Data Science Pipeline - Jul 14, 2017.
Start with y. Concentrate on formalizing the predictive problem, building the workflow, and turning it into production rather than optimizing your predictive model. Once the former is done, the latter is easy.
- Marketing Analytics for Data Rich Environments - Jul 14, 2017.
A lot is changing in the world of marketing analytics. Marketing scientist Kevin Gray asks Professor Michel Wedel, a leading authority on this topic from the Robert H. Smith School of Business at the University of Maryland, what marketing researchers and data scientists most need to know about it.
- DataScience: Elevate Live Stream, July 27 - Jul 13, 2017.
Register now for the live stream of DataScience: Elevate, a half-day event featuring data science leaders from Google, Netflix, eHarmony, and other global companies.
- The 4 Types of Data Analytics - Jul 13, 2017.
We focus on the four types of data analytics we encounter in data science: Descriptive, Diagnostic, Predictive and Prescriptive.
- Automated Machine Learning — A Paradigm Shift That Accelerates Data Scientist Productivity - Jul 13, 2017.
There is a growing community around creating tools that automate many machine learning tasks, as well as other tasks that are part of the machine learning workflow. The paradigm that encapsulates this idea is often referred to as automated machine learning.
- Top KDnuggets tweets, Jul 05-11: 10 Free Must-Read Books for #MachineLearning and #DataScience; Why AI and Machine Learning? - Jul 12, 2017.
Also great overview: Unintuitive properties of #NeuralNetworks; #Apache #Flink vs #Spark: The Strange Loop in #DeepLearning - the coolest idea in #MachineLearning in 20 yrs;
- Turn Data to Gold: Deploy Real-Time Analytics to Maximize Insurance IoT (Webinar, July 25) - Jul 12, 2017.
Join experts from leading firms for discussion how to take advantage of future insurance opportunities using the key to unlocking IoT data – real-time analytics.
- CAN (Creative Adversarial Network) - Explained - Jul 12, 2017.
GANs (Generative Adversarial Networks), a type of Deep Learning networks, have been very successful in creating non-procedural content. This work explores the possibility of machine generated creative content.
- The Guerrilla Guide to Machine Learning with Julia - Jul 12, 2017.
This post is a lean look at learning machine learning with Julia. It is a complete, if very short, course for the quick study hacker with no time (or patience) to spare.
- Become an active part of the analytics community - Jul 11, 2017.
Invest in your career with IAPA Individual Membership and become an active part of the analytics community.
- Become a data scientist at Northwestern – online - Jul 11, 2017.
Develop the skills and expertise needed for the fast-growing Data Science field with courses focused on modeling, business management, communications, and IT.
- Top June Stories: Top 15 Python Libraries for Data Science in 2017 - Jul 11, 2017.
Also 6 Interesting Things You Can Do with Python on Facebook Data; 7 Steps to Mastering Data Preparation with Python.
- Why Every Company Needs a Digital Brain - Jul 11, 2017.
As emerging technologies like AI/machine learning are adopted across different parts of the business, enterprises require a “digital brain” to coordinate those efforts and generate systemic intelligence.
- Medical Image Analysis with Deep Learning , Part 4 - Jul 11, 2017.
This is the fourth installment of this series, and covers medical images and their components, medical image formats and their format conversions. The goal is to develop knowledge to help us with our ultimate goal — medical image analysis with deep learning.
- The Strange Loop in Deep Learning - Jul 11, 2017.
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.”
- JupyterCon – Collaborative Data Science, New York, August 22-25 - Jul 10, 2017.
Bloomberg, Microsoft, Netflix and others found how Jupyter Notebook - the new front end for collaborative data science - make data a competitive advantage. Save an extra 20% with code PCKDNG.
- What Are Artificial Intelligence, Machine Learning, and Deep Learning? - Jul 10, 2017.
AI and Machine Learning have become mainstream, and people know shockingly little about it. Here is an explainer and useful references.
- Predictive Analytics Times – Highlighted Exclusives - Jul 10, 2017.
Analytics 101: Assessing Project Value, Employee Life Time Value and Cost Modeling, Closing the Loop with Predictive Product Performance, and more.
- Data Science Governance - Why does it matter? Why now? - Jul 10, 2017.
Everyone is talking about GDPR, Data Governance and Data Privacy, these days. Here we discuss what is it and why does it matter.
- Top Stories Jul 3-9: Applying Deep Learning to Real-world Problems; Advice to your younger Data Scientist Self? - Jul 10, 2017.
Also Top 15 Python Libraries for Data Science in 2017; Apache Flink: The Next Distributed Data Processing Revolution?
- 5 Free Resources for Getting Started with Self-driving Vehicles - Jul 10, 2017.
This is a short list of 5 resources to help newcomers find their bearings when learning about self-driving vehicles, all of which are free. This should be sufficient to learn the basics, and to learn where to look next for further instruction.
- New Poll: Will society become better from increased automation, AI, and Machine Learning? - Jul 9, 2017.
What will be the impact on human society and human welfare of increased automation, AI, and Machine Learning? Please vote.
- Upcoming Meetings in Analytics, Big Data, Data Science, Machine Learning: July and Beyond - Jul 8, 2017.
Coming soon: 61st World Statistics Congress Marrakech, TDWI Anaheim, ICML Sydney, KDD-2017 Halifax, JupyterCon NYC, Big Data Innovation Summit Boston, and many more.
- Analytically Speaking Featuring Pedro Saraiva, July 12 - Jul 7, 2017.
Former academician and now Portugal MP Pedro Saraiva says that Parliaments and societies will improve if more people with a good statistical background become MP. Learn about the paradoxes and issues in statistics and politics.
- Improving Zillow Zestimate with 36 Lines of Code - Jul 7, 2017.
We built this project as a quick and easy way to leverage some of the amazing technologies that are being built by the data science community!
- Exploratory Data Analysis in Python - Jul 7, 2017.
We view EDA very much like a tree: there is a basic series of steps you perform every time you perform EDA (the main trunk of the tree) but at each step, observations will lead you down other avenues (branches) of exploration by raising questions you want to answer or hypotheses you want to test.
- Inference Made Simple – Applying the reasoning power of GRAKN.AI to find new knowledge about the world - Jul 7, 2017.
This article aims to provide an overview of getting started with GRAKN.AI, and provides a simple example of how to write inference rules using Graql.
- Deploying Data Science Projects [Whitepaper] - Jul 6, 2017.
In a new whitepaper from Team Anaconda, Productionizing and Deploying Data Science Projects, our data science experts share the factors to consider when deploying data science projects, how to leverage Anaconda Project to encapsulate your data science projects, and more.
- Happy 4th of July from Chief Analytics Officer, Fall - Jul 6, 2017.
The sell out event for C-Level data and analytics executives in North America: 300+ delegates, 120+ speakers, 4 days of content, Boston, Oct 2-5, 2017. Use code 4JULY to save.
- Usage Patterns and the Economics of the Public Cloud - Jul 6, 2017.
Research in economics and operations management posits that dynamic pricing is critically important when capacity is fixed (at least in the short run) and fixed costs represent a substantial fraction of total costs.
- Generali, The Co-operators, La Mutuelle Generale and IBM on using AI to lower operational costs – Exclusive webinar - Jul 6, 2017.
Learn how insurers can use AI and Machine Learning to improve operational efficiencies, lower costs and improve productivity in this webinar on July 20.
- Connecting with the Internet of Things - Jul 6, 2017.
If you’re like me, you've heard a lot about the Internet of Things (IoT) but are confused about what it really is.
- Top KDnuggets tweets, Jun 28-Jul 4: Cheat Sheet of #MachineLearning and #Python Cheat Sheets; Learning #DeepLearning with #Keras - Jul 5, 2017.
Also: Train your #deeplearning model faster and sharper — two novel techniques; Lecture Collection - Natural Language Processing with #DeepLearning (Winter 2017) [Stanford]; #ICYMI 10 Free Must-Read Books for #MachineLearning and #DataScience
- Predictive Analytics Is Taking Over The World - Jul 5, 2017.
Since 2009, Predictive Analytics World has delivered the heart of data science - driving predictive value from data - by featuring the most in-house leading practitioners from brand-name organizations. In 2017, we’ve lined up the best and brightest - and that can include you.
- Getting Started with Python for Data Analysis - Jul 5, 2017.
A guide for beginners to Python for getting started with data analysis.
- Apache Flink: The Next Distributed Data Processing Revolution? - Jul 5, 2017.
Will Apache Flink displace Apache Spark as the new champion of Big Data Processing? We compare Spark and Apache Flink performance for batch processing and stream processing.
- What Advice Would You Give Your Younger Data Scientist Self? - Jul 5, 2017.
I was asked this question recently via LinkedIn message: "What advice would you give your younger data scientist self?" The best piece of advice I honestly think I can give is this: Forget about "data science."
- Text Clustering : Quick insights from Unstructured Data, part 2 - Jul 4, 2017.
We will build this in a modular way and also focus on exposing the functionalities as an API so that it can serve as a plug and play model without any disruptions to the existing systems.
- Spotlight on the Remarkable Potential of AI in KYC (Know Your Customer) - Jul 4, 2017.
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.
- How Feature Engineering Can Help You Do Well in a Kaggle Competition – Part 3 - Jul 4, 2017.
In this last post of the series, I describe how I used more powerful machine learning algorithms for the click prediction problem as well as the ensembling techniques that took me up to the 19th position on the leaderboard (top 2%)
- Top /r/MachineLearning Posts, June: NumPy Gets Funding; ML Cheat Sheets For All; Hot Dog or Not?!? - Jul 3, 2017.
NumPy receives first ever funding, thanks to Moore Foundation; Cheat Sheets for deep learning and machine learning; How HBO’s Silicon Valley built “Not Hotdog” with mobile TensorFlow & Keras; Andrej Karpathy leaves OpenAI for Tesla; Machine, a machine learning IDE
- Top Stories, Jun 26-Jul 2: Top 10 Quora Machine Learning Writers and Their Best Advice; Applying Deep Learning to Real-world Problems - Jul 3, 2017.
Top 10 Quora Machine Learning Writers and Their Best Advice, Updated, Applying Deep Learning to Real-world Problems; Using the TensorFlow API: An Introductory Tutorial Series; Text Clustering: Get quick insights from Unstructured Data; Why Artificial Intelligence and Machine Learning?
- Deep Learning Zero to One: 5 Awe-Inspiring Demos with Code for Beginners, part 2 - Jul 1, 2017.
Here are deep learning examples and demos you can just download and run, including Spotify Artist Search using Speech APIs, Symbolic AI Speech Recognition, and Algorithmia API Photo Colorizer.
The BI & Data Analysis Conundrum: 8 Reasons Why Many Big Data Analytics Solutions Fail to Deliver Value
6 Reasons Why Python Is Suddenly Super Popular
When not to use deep learning
The 4 Types of Data Analytics
Jun
