Also: #NeuralNetwork #AI is simple. So... Stop pretending; 5 Free Resources for Getting Started with #DeepLearning for Natural Language Pro; Want a Job in #Data? Learn This
Predictive policing uncovers racial inequity, which it threatens to perpetuate - but, if we turn things around, it also presents an unprecedented opportunity to advance social justice.
Calling all coders and data scientists to join McKinsey 24-hour hackathon on March 10, 2018. Win All-expenses paid trip to a tech conference of your choice.
Over the past decade, the field of artificial intelligence (AI) has seen striking developments. As surveyed in, there now exist over twenty domains in which AI programs are performing at least as well as (if not better than) humans.
Python facilitates different approaches to writing code, and while an object-oriented approach is common, an alternative and useful style of writing code is functional programming.
We compare Gartner 2018 Magic Quadrant for Data Science, Machine Learning Platforms vs its 2017 version and identify notable changes for leaders and challengers, including IBM, SAS, RapidMiner, KNIME, Alteryx, H2O.ai, and Domino.
Open Data Science Conference just released 80% of their schedule and the first round of speakers for ODSC East 2018 in Boston, May 1-4. Learn, train and engage with 200+ world class experts. Save 50% with code KDNUGGETS.
Predictive Analytics World for Business is heading to Las Vegas, NV on June 3-7, 2018 and we're excited about the stellar speaker line-up, a diverse array of industry leading professionals.
The most common complaints we see from candidates who have faced rejection are lack of experience, education level requirements, lack of opportunities for Freshers, overly demanding and confusing job role requirements.
This article explains the synergy between DevOps and Machine Learning and their applications like tracking application delivery, troubleshooting and triage analytics, preventing production failures, etc.
Predictive Analytics World for Industry 4.0 is coming to Munich, 12-13 Jun 2018. Find the latest trends and technologies in machine & deep learning for the era of Internet of Things and artificial intelligence. Super Early Bird Rates end Mar 2.
Big Data revolution led to the explosion in Data Centers, which are consuming energy at increasingly higher rate. This blog reviews 2 standard methods for improving data center efficiency and argues that 3rd method - Machine Learning - is the best solution.
Also: Want a Job in Data? Learn This; A Comparative Analysis of Top 6 BI and Data Visualization Tools in 2018; 5 Fantastic Practical Natural Language Processing Resources; Neural network AI is simple
Build enterprise-grade functionally rich Spark applications with the aid of an intuitive drag-and-drop user interface and a wide array of pre-built Spark operators.
Read Gartner 2018 Magic Quadrant for Data Science and Machine Learning Platforms, courtesy of Domino, and learn which data science platform is right for your organization and why Domino was named a Visionary.
Control structures allow you to specify the execution of your code. They are extremely useful if you want to run a piece of code multiple times, or if you want to run a piece a code if a certain condition is met.
Join us in San Francisco or London this Spring the next chapters of the World-renowned Data & Analytics Innovation Summits. Bringing together the top minds in Big Data and Analytics industry. Use code KD200 to get £/$200 off any two-day pass.
This article provides a short overview of emerging data scientist types and their unique skillsets, as well as a guide for HR professionals and analytics managers who are looking to hire their first data scientists or build a data science team. Included are an overview of skills for each type and specific questions that can be asked to assess candidates.
In this article, we will compare the most commonly used platforms and analyze their main features to help you choose one or several platforms that will provide indispensable aid for your work communication.
#NeuralNetwork #AI is simple. Stop pretending you are a genius; Cartoon: #ValentinesDay or #MachineLearning Problems in 2118; #MachineLearning Top 10 Open Source Projects.
We examine two main types of recommender systems: Content based and Collaborative filtering. Both have their pros and cons depending upon the context in which you want to use them.
Join the leading minds in AI, explore AI latest developments, separate hype from reality, and learn how to apply AI in your organization right now. Use code PCKDNG. Early price ends Mar 16.
Predictive Analytics World and Deep Learning World conferences are coming to Caesars Palace in Las Vegas, Jun 3-7. It's not too late to save with the Early Bird and attend the biggest PAW mega-event ever.
Strata gives you the tools, skills, and intel to stay ahead in the rapidly evolving field of data. Best price till Fri, Feb 23, 2018. Also, save 20% on Strata San Jose with code KDNU.
We update the top AI and Machine Learning projects in Python. Tensorflow has moved to the first place with triple-digit growth in contributors. Scikit-learn dropped to 2nd place, but still has a very large base of contributors.
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.
The inaugural Deep Learning World heads to Caesar's Palace Las Vegas, Jun 3-7, alongside Predictive Analytics World. Early Bird pricing ends Friday – Register now!
Here are 5 useful things to know about Data Science, including its relationship to BI, Data Mining, Predictive Analytics, and Machine Learning; Data Scientist job prospects; where to learn Data Science; and which algorithms/methods are used by Data Scientists
What do Amazon, Facebook, Google, IBM, Microsoft and Twitter have in common? They're all adopters of graph databases - a hot technology that continues to evolve.
Interested in learning the concepts behind Logistic Regression (LogR)? Looking for a concise introduction to LogR? This article is for you. Includes a Python implementation and links to an R script as well.
We discuss supervised learning, unsupervised learning and reinforcement learning, neural networks, and 6 reasons that helped AI Research and Development to move ahead.
The IEEE Big Data conference series started in 2013 has established itself as the top tier research conference in Big Data. We invite industrial, government, and academic organizations to submit proposals to organize a Data Challenge for the 2018 IEEE International Conference on Big Data.
This webinar will give you the insights to stay ahead of the curve of innovation, including Real-Time Risk Assessment, Automatically Turning Data to Action, and more.
In the spirit of Valentine's Day, we want to show you the love - data love. Use coupon KDLOVE25 and save 25% on all individual Online Learning courses*, now through February 26!
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.
In order to understand how to estimate LTV, it is useful to first think about evaluating a customer’s lifetime value at the end of their relationship with us.
At AnacondaCON 2018, Apr 8-11 in Austin, our passionate community of data scientists, IT professionals, analysts, developers, and business leaders will come together for 45+ talks on data science, machine learning, AI, and more. Early Bird offer - 2 tickets for price of one before Feb 28!
Also: Transfer Learning using differential learning rates; Which #MachineLearning #Algorithm be used in year 2118? We explain why it will be #Regression; 5 Fantastic Practical #MachineLearning Resources
Join MADS: Marketing Analytics and Data Science in San Francisco, Apr 11-13, hear first-hand from industry thought leaders and experts on how to navigate the challenges and succeed at making data work for YOU! Save 20% with VIP Code MADS18KDN
Understanding where and how AI will impact insurance is crucial to deliver growth and true business value. Download the whitepaper “Insurance AI – The Roadmap to Impact” which includes partners' AI plans for 2020 and which steps they are taking today to achieve this vision.
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.
This project is second phase of my popular project - Is Google Tensorflow Object Detection API the easiest way to implement image recognition? Here I extend the API to train on a new object that is not part of the COCO dataset.
One of the gems that I felt needed to be written down from Ng's deep learning courses is his general recipe to approaching a deep learning algorithm/model.
Download a free copy of the white paper The 7 Steps to Driving a Successful Data Science POC for a detailed walk-through of the seven steps to running a successful POC.
DataScience: Elevate will be held Feb 22 in San Francisco. Register to be a part of a full day of panels and presentations from people and companies at the forefront of data science.
CNBC recently quoted this KDnuggets interview which discussed how United States Olympic Committee uses Big Data, how athletes respond to Analytical insights, integration of sports medicine into sports performance and sports injury.
AI was compared to the discovery of fire, but its impact hinges on how creative we are with the technology—just like it did for early humans employing fire. Here are four diverse examples of applied AI to get your creative juices flowing.
Also: Introduction to Python Ensembles; 5 Machine Learning Projects You Should Not Overlook; Top 15 Scala Libraries for Data Science in 2018; Fast.ai Lesson 1 on Google Colab (Free GPU); The Doing Part of Learning Data Science
Google Colaboratory is a promising machine learning research platform. Here are 3 tips to simplify its usage and facilitate using a GPU, installing libraries, and uploading data files.
The one-day conference includes 16 sessions across dedicated streams focusing on data and analytics, technology, customer experience & marketing strategy: Melbourne 23 Feb, Sydney 26 Feb.
Learn how AI and machine learning technology will expand adoption of service-service BI by making it easier for business users to answer ad hoc questions and perform advanced analysis on their own.
In this post, we'll take you through the basics of ensembles — what they are and why they work so well — and provide a hands-on tutorial for building basic ensembles.
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.
Change management may be seen as an opposite to data science, but in reality both are related. Without proper implementation, a data science project fails.
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!
In this post, I will demonstrate how to use Google Colab for fastai. You can use GPU as a backend for free for 12 hours at a time. GPU compute for free? Are you kidding me?
Also: Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples; Why Generalists Dominate #DataScience - an inconvenient truth; #ICYMI A Beginner’s Guide to Data Engineering – Part I
Designed specifically by, and for, senior software engineers, architects, and technical engineering managers, QCon.ai is a dedicated conference for AI and machine learning. Use code KDnuggets by Feb 17 to save.
Automating feature engineering optimizes the process of building and deploying accurate machine learning models by handling necessary but tedious tasks so data scientists can focus more on other important steps.
DataScience: Elevate will be held Feb 22 in San Francisco. Register now for the livestream to tune into a full day of panels and presentations from people and companies at the forefront of data science.
What do you think of this year’s predictions? Do you see any new tools on the horizon, or do you believe data science popularity is due for a reckoning of sorts?
This post presents 5 fantastic practical machine learning resources, covering machine learning right from basics, as well as coding algorithms from scratch and using particular deep learning frameworks.
Biometric identification is moving from the realm of high -tech movie scenes to everyday use. The science is already changing physical and cyber security.
Think 2018 is for those who seek inspiration and education, reinvention and innovation, want to connect with experts and seek progress. It is for understanding what is going on in the world around AI, Cloud, Data, Security, and Systems and discovering what’s possible. Use code TK18CAC to save.
Also: The 8 Neural Network Architectures Machine Learning Researchers Need to Learn; Avoid Overfitting with Regularization; Understanding Learning Rates and How It Improves Performance in Deep Learning; Comparing Machine Learning as a Service
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.
Coming soon: TDWI Las Vegas, BI + Analytics Huntington Beach, Strata San Jose, IBM Think Las Vegas, Big Data & Analytics Singapore, KNIME Berlin, Nvidia GPU, and more.
This article explains overfitting which is one of the reasons for poor predictions for unseen samples. Also, regularization technique based on regression is presented by simple steps to make it clear how to avoid overfitting.
Join DataRobot on Feb 15 to discover how Automated Machine Learning provides the ability to develop and refresh Customer 360 predictive models, the ability to deploy models with a click of a button, and more!
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.
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.
How data science can improve retail
Introduction to Functional Programming in Python
Gainers and Losers in Gartner 2018 Magic Quadrant for Data Science and Machine Learning Platforms
A Comparative Analysis of Top 6 BI and Data Visualization Tools in 2018
Top 20 Python AI and Machine Learning Open Source Projects
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