All (100) | Courses, Education (10) | Meetings (11) | News, Features (13) | Opinions, Interviews (26) | Software (6) | Tutorials, Overviews (31) | Webcasts & Webinars (3)
- Optimization in Machine Learning: Robust or global minimum? - Jun 30, 2017.
Here we discuss how convex problems are solved and optimised in machine learning/deep learning.
- Why Artificial Intelligence and Machine Learning? - Jun 30, 2017.
With your goals (i.e., the why) in mind, the next step for any artificial intelligence or machine learning solution is to specify how (e.g., which algorithms or models to use) to achieve a specific goal or set of goals, and finally what the end result will be (e.g., product, report, predictive model).
- Applying Deep Learning to Real-world Problems - Jun 30, 2017.
In this blog post I shared three learnings that are important to us at Merantix when applying deep learning to real-world problems. I hope that these ideas are helpful for other people who plan to use deep learning in their business.
- TDWI Accelerate: The Fastest Path to Achieving Your Analytics Goals, Seattle, Oct 16-18 - Jun 29, 2017.
Accelerate gives data visionaries like you expert guidance and insight to further your business and career goals, in just three days. Super Early Bird till Aug 25 - save 20% with code ACCKD01.
- Web Scraping with R: Online Food Blogs Example - Jun 29, 2017.
We consider scraping data from online food blogs to construct a data set of recipes with ingredients, nutritional information and more, and do exploratory analysis which provides tasty insights.
- Interesting Things Learned as a Student of Machine Learning - Jun 29, 2017.
Did you ever learn something you didn't really want to? The path to machine learning mastery is paved with such collateral knowledge. Here are a few examples of such information I have gleaned while trekking away.
- Who Cares About Evidence? - Jun 29, 2017.
Why bother with evidence? Because it improves the odds that what we believe is actually true. But not always.
- Top KDnuggets tweets, Jun 21-27: An Introduction to Key #DataScience Concepts; Emerging #BigData #DeepLearning #Python Ecosystem - Jun 28, 2017.
Also 5 #EBooks to Read Before Getting into #DataScience; Awesome Public Datasets on GitHub; The Data Science Process, Rediscovered.
- Text Clustering: Get quick insights from Unstructured Data - Jun 28, 2017.
Grouping and clustering free text is an important advance towards making good use of it. We present an algorithm for unsupervised text clustering approach that enables business to programmatically bin this data.
- Using the TensorFlow API: An Introductory Tutorial Series - Jun 28, 2017.
This post summarizes and links to a great multi-part tutorial series on learning the TensorFlow API for building a variety of neural networks, as well as a bonus tutorial on backpropagation from the beginning.
- For data scientists, now is the time to act; Forrester has insights to help you get started - Jun 27, 2017.
IBM, a leader in 2017 Forrester Wave Report for Predictive Analytics and Machine Learning Solutions, offers data scientists a complete toolkit, including predictive analytics and machine learning capabilities and more.
- Pitfalls in pseudo-random number sampling at scale with Apache Spark - Jun 27, 2017.
Large scale simulation of random number generation is possible with today’s high speed & scalable distributed computing frameworks. Let’s understand how it can be achieved using Apache Spark.
- How Feature Engineering Can Help You Do Well in a Kaggle Competition – Part 2 - Jun 27, 2017.
In this post, I describe the competition evaluation, the design of my cross-validation strategy and my baseline models using statistics and trees ensembles.
- Deep Learning with R + Keras - Jun 27, 2017.
Keras has grown in popularity and supported on a wide set of platforms including Tensorflow, CNTK, Apple’s CoreML, and Theano. It is becoming the de factor language for deep learning.
- Learn to Engage Customers the Disney Way at TDWI Anaheim, Aug 6-11 - Jun 26, 2017.
TDWI Anaheim is the leading event for Analytics, Big Data, and Data Science Training. Use code KD30 to save 30% through July 14 and check out our amazing speaker lineup.
- Predictive Analytics World is back in London! - Jun 26, 2017.
The leading vendor-neutral conference about predictive analytics is holding its seventh annual conference this October 11-12. Once again it's time for all predictive analytics smartest minds to gather and explore all the latest.
- Deep Learning Zero to One: 5 Awe-Inspiring Demos with Code for Beginners - Jun 26, 2017.
Here are deep learning demos and examples you can just download and run. No Math. No Theory. No Books.
- Top Stories, Jun 19-25: Emerging Ecosystem: Data Science & Machine Learning Software, Analyzed; Machine Learning Algorithms in Self-Driving Cars - Jun 26, 2017.
Emerging Ecosystem: Data Science and Machine Learning Software, Analyzed; The Machine Learning Algorithms Used in Self-Driving Cars; The world’s first protein database for Machine Learning and AI; Making Sense of Machine Learning; 75 Big Data Terms to Know to Make your Dad Proud
- Top 10 Quora Machine Learning Writers and Their Best Advice, Updated - Jun 26, 2017.
Gain some insight on a variety of topics with select answers from Quora's current top machine learning writers. Advice on research, interviews, hot topics in the field, how to best progress in your learning, and more are all covered herein.
- Why Data Science Argues against a Muslim Ban - Jun 24, 2017.
From the perspective of data science, a Muslim ban would weaken security, not strengthen it.
- DataScience.com, H2O.ai Partner to Bring AI Capabilities to Enterprise Data Science Teams - Jun 23, 2017.
DataScience.com Platform customers can now easily deploy artificial intelligence and deep learning models built with H2O.ai’s open source AI platform.
- 3 Key Trends Shaping the 2017 Data Science Hiring Market - Jun 23, 2017.
Interesting finding include: salaries for early career data scientists decrease for the first time in four years, percent of early career data scientists with a PhD drops - read more for details.
- Will Apache Spark Finally Advance Genomic Data Analysis? - Jun 23, 2017.
Spark has been useful in mapping out genetic traits that can be associated with certain diseases and the genetic makeup of microorganisms that live in our bodies.
- Spark with Scala – ACM Professional Development Seminar, Santa Clara, Aug 5 - Jun 22, 2017.
This class will introduce Apache Spark 2, focusing on using it for data analysis Taught by Sujee Maniyam on behalf of the local ACM chapter, SFbayACM.
- The world’s first protein database for Machine Learning and AI - Jun 22, 2017.
dSPP is the world first interactive database of proteins for AI and Machine Learning, and is fully integrated with Keras and Tensorflow. You can access the database at peptone.io/dspp
- Taxonomy of Methods for Deep Meta Learning - Jun 22, 2017.
This post discusses a variety of contemporary Deep Meta Learning methods, in which meta-data is manipulated to generate simulated architectures. Current meta-learning capabilities involve either support for search for architectures or networks inside networks.
- Golden State Warriors Analytics Exercise - Jun 22, 2017.
This post outlines a data analysis exercise undertaken by students in a recent University of San Francisco MBA class, in which they were forced to make difficult data science trade-offs between gathering data, preparing the data and performing the actual analysis.
- Top KDnuggets tweets, Jun 14-20: 5 EBooks to Read Before Getting into A Data Science or Big Data Career - Jun 21, 2017.
Also 10 Free Must-Read Books for #MachineLearning and #DataScience; #Keras implementation of a simple Neural Net module for relational reasoning; Applying #deeplearning to real-world problems
- Emerging Ecosystem: Data Science and Machine Learning Software, Analyzed - Jun 21, 2017.
We examine which top tools are "friends", their Python vs R bias, and which work well with Spark/Hadoop and Deep Learning, and identify an emerging Big Data Deep Learning ecosystem.
- Making Sense of Machine Learning - Jun 21, 2017.
Broadly speaking, machine learners are computer algorithms designed for pattern recognition, curve fitting, classification and clustering. The word learning in the term stems from the ability to learn from data.
- Predictive analytics sparks sizable bottom-line benefits - Jun 20, 2017.
Learn more about how the power of IBM SPSS predictive analytics can help you transform your business while boosting your bottom line.
- What if that pretty chart is just plain wrong? - Jun 20, 2017.
As businesses grow, the tools and technologies they rely on must either evolve with them, or be replaced. Tools that worked for a team of 10 may no longer for a team of 50 or more.
- AI for fintech course – Early discounts and limited places - Jun 20, 2017.
This new course with limited places will focus on AI design (product, development and Data) for the fintech industry and will be taught online by Ajit Jaokar and Jakob Aungiers.
- Why Swarm Intelligence is a Better Way to Read Emotions - Jun 20, 2017.
Swarm Intelligence is using many simple machine learning models good at one small task to solve bigger, more complex problems. We examine how it can improve sentiment analysis and measuring emotions.
- Role of the Data Scientist in the B2B Era - Jun 20, 2017.
In businesses everywhere, the digital transformation is spawning a bunch of new job titles. Among them are Chief Data Officer, Big Data Architect and Data Visualizer. All these sought-after specialist data roles are having a major impact on the workplace.
- Does Machine Learning Have a Future Role in Cyber Security? - Jun 20, 2017.
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.
- Best Data Science Courses from Udemy (only $10 till June 21) - Jun 19, 2017.
Here are some of the best courses in data science from Udemy, covering Data Science, Machine Learning, Python, Spark, Tableau, and Hadoop - only $10 until June 21, 2017.
- 75 Big Data Terms to Know to Make your Dad Proud - Jun 19, 2017.
Here is a good list of 75 Big Data terms you can use to impress your father, even if you already bought him a gift.
- The Machine Learning Algorithms Used in Self-Driving Cars - Jun 19, 2017.
Machine Learning applications include evaluation of driver condition or driving scenario classification through data fusion from different external and internal sensors. We examine different algorithms used for self-driving cars.
- Top Stories, Jun 12-18: Top 15 Python Libraries for Data Science in 2017; Deep Learning Papers Reading Roadmap - Jun 19, 2017.
Top 15 Python Libraries for Data Science in 2017; Deep Learning Papers Reading Roadmap; The Practical Importance of Feature Selection; Understanding Deep Learning Requires Re-thinking Generalization; K-means Clustering with Tableau
- Analytics Professionals: Get recognised, further your career, reduce your tax - Jun 18, 2017.
You can be recognised for your skills in data analytics in just six weeks by IAPA. Act before 30 June and claim the cost of the IAPA-certified via credential as a tax deduction.
- MSc in Applied Data Science, Big Data – Online and Part-time - Jun 16, 2017.
Data ScienceTech Institute is the 1st private postgraduate school in pure Data Science & Big Data education in France! Data ScienceTech Institute's mission is simple: training executive students to become ready-to-go Read more »
- Chief Analytics Officer, Fall returns bigger and better in 2017 - Jun 16, 2017.
Chief Analytics Officer, Oct 2-5 in Boston, will be the largest, most senior gathering of analytics leaders in North America, providing a platform for over 300+ attendees and 125+ speakers to share best practice and explore strategies for driving actionable insights through analytics. Special KDnuggets offer - book by June 23.
- The Real “Fear” of AI is Automation Inundation - Jun 16, 2017.
The biggest threat to minimum wage earners (and beyond, quite frankly) is the new tsunami of automation in the workplace.
- K-means Clustering with Tableau – Call Detail Records Example - Jun 16, 2017.
We show how to use Tableau 10 clustering feature to create statistically-based segments that provide insights about similarities in different groups and performance of the groups when compared to each other.
- Understanding Deep Learning Requires Re-thinking Generalization - Jun 16, 2017.
What is it that distinguishes neural networks that generalize well from those that don’t? A satisfying answer to this question would not only help to make neural networks more interpretable, but it might also lead to more principled and reliable model architecture design.
- Machine learning made simple with Apache Spark - Jun 15, 2017.
Powered by Apache Spark, Databricks provides an end-to-end platform designed to help data engineers and data scientists easily implement advanced analytics at scale. Download the Making Machine Learning Simple Whitepaper from Databricks to learn more.
- Hadoop as a Data Warehouse: Cracking the Code with Kudu - Jun 15, 2017.
Here we discuss problems behind replacing an existing Data Warehouse with Hadoop and available solutions to make this happen. Lets see how.
- The Surprising Complexity of Randomness - Jun 15, 2017.
The reason we have pseudorandom numbers is because generating true random numbers using a computer is difficult. Computers, by design, are excellent at taking a set of instructions and carrying them out in the exact same way, every single time.
- Medical Image Analysis with Deep Learning , Part 3 - Jun 15, 2017.
In this article we will focus — basic deep learning using Keras and Theano. We will do 2 examples one using keras for basic predictive analytics and other a simple example of image analysis using VGG.
- Top KDnuggets tweets, Jun 07-13: Is Regression Analysis Really Machine Learning? - Jun 14, 2017.
Machine Learning in Real Life: Tales from the Trenches; Is Regression Analysis Really Machine Learning?; Implementing Your Own k-Nearest Neighbour Algorithm Using Python; Building Simple Neural Networks - TensorFlow for Hackers.
- Live Immersive Predictive Analytics,
Data Science Experiential Training - Jun 14, 2017.Successful analytics at the organizational-level starts with immersive, interactive training and goal-driven strategy. TMA’s live online and classroom training spans all skill levels and analytic team roles to build analytic leaders. Seattle in July, Live online in September, and Wash-DC in October.
- Data Scientist: Learn the Skills you need for free - Jun 14, 2017.
Data Scientists are in big demand! We review career pathways, relevant data science skills, and how you can learn them at no cost.
- Open Innovation and Crowdsourcing in Machine Learning – Getting premium value out of data - Jun 14, 2017.
Recently, PSL Research University launched a one-week course combining theoretical lectures and practical sessions. 115 students from various backgrounds and skill levels were enrolled; something quite spectacular happened during the week: Students have achieved an astounding level of score improvement - in just three afternoons.
- 7 Ways to Get High-Quality Labeled Training Data at Low Cost - Jun 13, 2017.
Having labeled training data is needed for machine learning, but getting such data is not simple or cheap. We review 7 approaches including repurposing, harvesting free sources, retrain models on progressively higher quality data, and more.
- Webinar: Forecast Demand in R With DataScience.com + RStudio, June 15 - Jun 13, 2017.
DataScience.com and RStudio are co-hosting a free webinar on June 15 to showcase how RStudio’s suite of tools for R seamlessly integrate with the DataScience.com Platform.
- Stay Up-To-Date on Predictive Analytics for Financial in NYC - Jun 13, 2017.
Come see top experts and practitioners present at Predictive Analytics World for Financial this October 29-November 2 in New York City. Minimize risk and multiply returns with data science!
- Top May Stories: KDnuggets Poll: Software for Analytics, Data Science, Machine Learning; How to Learn Machine Learning in 10 Days - Jun 13, 2017.
Also Machine Learning Workflows in Python from Scratch Part 1: Data Preparation; Deep Learning - Past, Present, and Future
- Top 15 Python Libraries for Data Science in 2017 - Jun 13, 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.
- Deep Learning Papers Reading Roadmap - Jun 13, 2017.
The roadmap is constructed in accordance with the following four guidelines: from outline to detail; from old to state-of-the-art; from generic to specific areas; focus on state-of-the-art.
- Sentiment, Emotional and Behavioral Analytics AND AI in Marketing Symposium, San Francisco, July 17-19 - Jun 12, 2017.
Learn from early-adopting marketing practitioners, AI technology developers, and industry analysts with their fingers on the pulse of this developing technology. Save with code KDN15.
- Data Mining Techniques, Free Chapter: Derived Variables – Making the Data Mean More - Jun 12, 2017.
Download this chapter by Gordon Linoff and Michael Berry, and learn how to create derived variables, which allow the statistical modeling process to incorporate human insights.
- The Latest on Predictive Analytics for Financial - Jun 12, 2017.
You know how much value and insight Predictive Analytics World offers and we want you to be among the first to know what’s on tap October 29-November 2, 2017 in New York City.
- The Practical Importance of Feature Selection - Jun 12, 2017.
Feature selection is useful on a variety of fronts: it is the best weapon against the Curse of Dimensionality; it can reduce overall training times; and it is a powerful defense against overfitting, increasing generalizability.
- Autonomous Vehicles Need Superhuman Perception for Success - Jun 12, 2017.
Michael Milford, Associate Professor at Queensland University of Technology (QUT), is a leading robotics researcher working to improve perception and more in autonomous vehicles, conducting his research at the intersection of robotics, neuroscience and computer vision.
- Top Stories, Jun 5-11: Is Regression Analysis Really Machine Learning?; 6 Interesting Things You Can Do with Python on Facebook Data - Jun 12, 2017.
Is Regression Analysis Really Machine Learning?; 6 Interesting Things You Can Do with Python on Facebook Data; A Practical Guide to Machine Learning; K-means Clustering with R: Call Detail Record Analysis; Machine Learning in Real Life: Tales from the Trenches to the Cloud
- DataScience.com and RStudio Have Partnered to Seamlessly Integrate RStudio Suite into the DataScience.com Platform - Jun 9, 2017.
With the RStudio integration, DataScience.com customers are able to write and run code in RStudio while benefitting from additional features of the platform: on-demand infrastructure, pre-configured environments, secret management, and more.
- Deep Learning: TensorFlow Programming via XML and PMML - Jun 9, 2017.
In this approach, problem dataset and its Neural network are specified in a PMML like XML file. Then it is used to populate the TensorFlow graph, which, in turn run to get the results.
- Top /r/MachineLearning Posts, May: Deep Image Analogy; Stylized Facial Animations; Google Open Sources Sketch-RNN - Jun 9, 2017.
Deep Image Analogy; Example-Based Synthesis of Stylized Facial Animations; Google releases dataset of 50M vector drawings, open sources Sketch-RNN implementation; New massive medical image dataset coming from Stanford; Everything that Works Works Because it's Bayesian: Why Deep Nets Generalize?
- A Practical Guide to Machine Learning: Understand, Differentiate, and Apply - Jun 9, 2017.
So, if Machine Learning was first defined in 1959, why is this now the time to seize the opportunity? It’s the economics.
- Business Analytics Grad Cert – Apply Now to Start in August - Jun 8, 2017.
Penn State World Campus offers a 9-credit Business Analytics Graduate Certificate and 30-credit online Master's Degree in Data Analytics - Business Analytics Option. Register now to start in August.
- New Speakers Announced for the European Machine Intelligence Summit & Machine Intelligence in Autonomous Vehicles Summit in Amsterdam, 28-29 June - Jun 8, 2017.
Explore the cutting-edge technology leading the way in Machine Intelligence and Autonomous Vehicles and it’s applications in industry at the Amsterdam Summits on June 28th & 29th. Use the discount code KDNUGGETS to save 20% on all tickets.
- Prepare Your Organization for Smooth AI Adoption - Jun 8, 2017.
Download this free whitepaper on how to prepare your company for all the challenges that it may face on the way to data-driven prosperity.
- The Unintended Consequences of Machine Learning - Jun 8, 2017.
But with great power comes great responsibility. Let me tell you a story about the unintended consequences of well-meaning machine learning research.
- How Feature Engineering Can Help You Do Well in a Kaggle Competition – Part I - Jun 8, 2017.
As I scroll through the leaderboard page, I found my name in the 19th position, which was the top 2% from nearly 1,000 competitors. Not bad for the first Kaggle competition I had decided to put a real effort in!
- Machine Learning in Real Life: Tales from the Trenches to the Cloud – Part 1 - Jun 8, 2017.
We live in a world where everyone knows enough about the Buzzwords “Deep Learning” and “Big Data”... we also live in a world where if you’re a developer you can, while knowing nothing about machine learning, go from zero to training a OCR model in the space of an hour.
- Top KDnuggets tweets, May 31-Jun 6: Essential Cheat Sheets for #MachineLearning and #DeepLearning - Jun 7, 2017.
The Artificial #ArtificialIntelligence Bubble and the Future of #Cybersecurity; Which #MachineLearning #Algorithm Should I Use? A handy #cheatsheet; 50 Companies Leading The #AI Revolution, Detailed; #MachineLearning Workflows in #Python from Scratch Part 1: Data Preparation
- Your Checklist to Get Data Science Implemented in Production - Jun 7, 2017.
For over a year we surveyed thousands of companies from all types of industries and data science advancement on how they managed to overcome these difficulties and analyzed the results. Here are the key things to keep in mind when you're working on your design-to-production pipeline.
- How HR Managers Use Data Science to Manage Talent for Their Companies - Jun 7, 2017.
Data sciences can also be used by HR manager to create several estimates like the investment on talent pool, cost per hire, cost on training, and cost per employee. It provides better techniques for optimization, forecasting, and reporting.
- Machine Learning Workflows in Python from Scratch Part 2: k-means Clustering - Jun 7, 2017.
The second post in this series of tutorials for implementing machine learning workflows in Python from scratch covers implementing the k-means clustering algorithm.
- Latest in Data and Analytics Training, Anaheim – 3 Steps to Convince Your Boss - Jun 6, 2017.
TDWI, the leading event for big data, data science & analytics training, comes to Anaheim, Aug 6-11. Save 30% through June 16 with priority code KD30.
- DataRobot Webinar on June 27, 2017: Automated Machine Learning in Action - Jun 6, 2017.
In this webinar, learn how DataRobot automates predictive modeling, and how our platform can deliver these same types of insights and a substantial productivity boost to your machine learning endeavors.
- Stay ahead of cyberattacks and fraud with predictive analytics - Jun 6, 2017.
Even as cyber criminals and swindlers step up their game, companies can use predictive analytics to stay ahead. Discover the full scope of IBM SPSS predictive analytics capabilities.
- 6 Interesting Things You Can Do with Python on Facebook Data - Jun 6, 2017.
Facebook has a huge amount of data that is available for you to explore, you can do many things with this data. I will be sharing my experience with you on how you can use the Facebook Graph API for analysis with Python.
- K-means Clustering with R: Call Detail Record Analysis - Jun 6, 2017.
Call Detail Record (CDR) is the information captured by the telecom companies during Call, SMS, and Internet activity of a customer. This information provides greater insights about the customer’s needs when used with customer demographics.
- NYU Stern MS in Business Analytics - Jun 5, 2017.
This one-year, part-time program is divided into five onsite modules: three in NYC and two in rotating global locations. Our first application deadline for the new incoming class is August 1, 2017.
- Predictive Analytics World NYC – Agenda announcement! - Jun 5, 2017.
Predictive Analytics World for Business & Predictive Analytics World for Financial Services come to New York, Oct. 29 - Nov. 2. Register now at Super Early Bird rates!
- Women in Tech: Interview with DeepMind’s Silvia Chiappa - Jun 5, 2017.
We interview leading women in STEM to learn more about how we can all work to make science and technology industries more inclusive. How can more women be encouraged to work in these fields?
- TPOT Automated Machine Learning Competition: Can AutoML beat humans on Kaggle? - Jun 5, 2017.
Over the next couple months, we’re going to challenge you to apply TPOT to any data science problem you find interesting on Kaggle. If your entry ranks in the top 25% of the leaderboard on a Kaggle problem, we want to see how TPOT helped you accomplish that.
- Top Stories, May 29-Jun 4: Machine Learning Workflows in Python from Scratch; Machine Learning Algorithms Cheat Sheet - Jun 5, 2017.
Machine Learning Workflows in Python from Scratch Part 1: Data Preparation; Which Machine Learning Algorithm Should I Use?; 7 Steps to Mastering Data Preparation with Python; 7 Techniques to Handle Imbalanced Data; Why Does Deep Learning Not Have a Local Minimum?
- Is Regression Analysis Really Machine Learning? - Jun 5, 2017.
What separates "traditional" applied statistics from machine learning? Is statistics the foundation on top of which machine learning is built? Is machine learning a superset of "traditional" statistics? Do these 2 concepts have a third unifying concept in common? So, in that vein... is regression analysis actually a form of machine learning?
- A Course in Semantic Technologies for Designing a Proof-of-Concept - Jun 2, 2017.
Ontotext live, online training designed to improve understanding of how Semantic Technology operates to help you make best use of it. Sign up by June 12 to save.
- Deep Learning 101: Demystifying Tensors - Jun 2, 2017.
Many deep-learning systems available today are based on tensor algebra, but tensor algebra isn’t tied to deep-learning. It isn’t hard to get started with tensor abuse but can be hard to stop.
- Why Does Deep Learning Not Have a Local Minimum? - Jun 2, 2017.
"As I understand, the chance of having a derivative zero in each of the thousands of direction is low. Is there some other reason besides this?"
- 7 Steps to Mastering Data Preparation with Python - Jun 2, 2017.
Follow these 7 steps for mastering data preparation, covering the concepts, the individual tasks, as well as different approaches to tackling the entire process from within the Python ecosystem.
- Machine Intelligence Summit & Autonomous Vehicles Track, Amsterdam – KDnuggets Offer - Jun 1, 2017.
RE•WORK's Machine Intelligence Summit and Machine Intelligence In Autonomous Vehicles Summit take place June 28-29 in Amsterdam. Save 20% with code KDNUGGETS.
- Which Machine Learning Algorithm Should I Use? - Jun 1, 2017.
A typical question asked by a beginner, when facing a wide variety of machine learning algorithms, is "which algorithm should I use?” The answer to the question varies depending on many factors, including the size, quality, and nature of data, the available computational time, and more.
- Upcoming Meetings in Analytics, Big Data, Data Science, Machine Learning: June and Beyond - Jun 1, 2017.
Coming soon: Spark Summit San Francisco, Open Data London, PAW Chicago, Big Data Toronto, O'Reilly AI NYC, Sentiment Symposium NYC, Postgres Vision Boston, and many more.
- The Artificial ‘Artificial Intelligence’ Bubble and the Future of Cybersecurity - Jun 1, 2017.
What’s going on now in the field of ‘AI’ resembles a soap bubble. And we all know what happens to soap bubbles eventually if they keep getting blown up by the circus clowns (no pun intended!): they burst.
- 7 Techniques to Handle Imbalanced Data - Jun 1, 2017.
This blog post introduces seven techniques that are commonly applied in domains like intrusion detection or real-time bidding, because the datasets are often extremely imbalanced.