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.
Join us in Las Vegas, June 3-7, 2018 and be there to witness these industry heavyweights share their knowledge in can't miss keynote sessions. Register by April 27 to save hundreds with current regular rates.
D3 is a JavaScript library that continues to grow, both in terms of popularity and possibilities, capable of creating dynamic, interactive visualisations. This tutorial provides a step-by-step guide on how to create a basic bar chart in d3, populated with data from a csv file.
Learn how make great visualizations using Dash with advanced data visualization workshops for Dash, R, Shiny and Dash R from April 14–15 in Boston, featuring Chris Parmer, the creator of Dash and co-founder of Plotly. Use code KDNUGGETS for 20% off.
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.
Tensorflow recently added new functionality and now we can extend the API to determine pixel by pixel location of objects of interest. So when would we need this extra granularity?
Also: #Data Skills: They’re Not Just for #DataScientists #DataScience; 50 Must-Read Books for #MachineLearning , #DeepLearning; #DataScience Lessons learned from #MarchMadness competition on @kaggle
The WCAI annual conference, Successful Applications of Customer Analytics is dedicated to real-world applications that balance high-level rigor and business know-how, and to elevating the role of analytics in an organization strategic decision-making.
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.
Strata Data Conferences bring together some of the world's smartest data scientists and business strategists. Join them in London and save with code PCKDNG.
Enhance your skill set with a data analytics degree — 100% online. Check out the 30-credit Master's in Data Analytics, delivered through Penn State World Campus.
Also: Introduction to k-Nearest Neighbors; Descriptive Statistics: The Mighty Dwarf of Data Science; 8 Common Pitfalls That Can Ruin Your Prediction; Will GDPR Make Machine Learning Illegal?; Top 20 Python AI and Machine Learning Open Source Projects
A Rosetta Stone of deep-learning frameworks has been created to allow data-scientists to easily leverage their expertise from one framework to another.
Data Science and Machine Learning are applicable very widely, so it is interesting to see how the application areas change. KDnuggets was running this question each year since 2006, so please vote and we will analyze the results and report the trends.
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.
Recently [we] were analyzing how different activation functions interact among themselves, and we found that using relu after sigmoid in the last two layers worsens the performance of the model.
Many underestimate the role of humans in successful deployment of AI solutions. Alegion engine produces AI training data and enables content moderation, sentiment analysis, data enrichment, tagging, categorization, and more.
Get the report on The Growing Influence of Analytics on the C-Suite Report and save with code KDN20 on Chief Analytics Officer, Spring in San Francisco.
The continued growth of big data, both in terms of quality and accessibility, is disrupting a wide range of roles. The skills needed to analyse this data need to be learned by everyone - not just data scientists.
Also: Reinforcement Learning Cheat Sheet; How to do #MachineLearning Efficiently; 6 Interesting Things You Can Do with #Python on #Facebook Data; Demystifying #Docker for #DataScientists
At AnacondaCON 2018 in Austin, Apr 8-11, you'll learn how data scientists are using GPUs for machine learning across a variety of applications and industries. The best part? One lucky attendee will receive a FREE NVIDIA TITAN V GPU!
A good prediction can help your work and make it easier. But how can you be sure that your prediction is good? Here are some common pitfalls that you should avoid.
This post is a short introductory overview of 12 Unix-like operating system command line tools of value to data science tasks, and the data scientists who perform them.
Learn how to build better models with support for multiple data sources and feature extraction at scale, simplify operations with on-demand cluster management, and more.
We examined 140 frameworks and distributed programing packages and came up with a list of top 20 distributed computing packages useful for Data Science, based on a combination of Github, Stack Overflow, and Google results.
No other mean of data description is more comprehensive than Descriptive Statistics and with the ever increasing volumes of data and the era of low latency decision making needs, its relevance will only continue to increase.
There are limits to what the state-of-the-art is capable of, which doesn’t mean that there aren’t tons of perfect use cases for machine learning, but does mean that you have to go into the process with your eyes open.
The courses cover topics such as Neural Networks and Deep Learning, Bayesian Networks, Big Data with Apache Spark, Bayesian Inference, Text Mining and Time Series. Each course has theoretical and practical classes, the latter done with R or Python.
We highlight recent developments in machine learning and Deep Learning related to multiscale methods, which analyze data at a variety of scales to capture a wider range of relevant features. We give a general overview of multiscale methods, examine recent successes, and compare with similar approaches.
Also: Introduction to Markov Chains; Introduction to Optimization with Genetic Algorithm; Top 5 Best Jupyter Notebook Extensions; Top 5 Best Jupyter Notebook Extensions; 5 Things to Know Before Rushing to Start in Data Science
In this tutorial, we'll teach you the basics of R by building a simple grade calculator. While we do not assume any R-specific knowledge, you should be familiar with general programming concepts.
Credit risk analytics in R will enable you to build credit risk models from start to finish, with access to real credit data on accompanying website, you will master a wide range of applications.
To help you become a Data Scientist, we put together a guide with answers to: how do you break into the profession? What skills do you need to become a data scientist? Where are best data science jobs?
The fast.ai library is a collection of supplementary wrappers for a host of popular machine learning libraries, designed to remove the necessity of writing your own functions to take care of some repetitive tasks in a machine learning workflow.
In this article, we show how to use Python libraries and HTML parsing to extract useful information from a website and answer some important analytics questions afterwards.
Join us in San Francisco or Chicago this spring for the next chapters of the World-renowned Data & Analytics Innovation events, bringing together the top minds in Big Data and Analytics across industries.
Google CoLaboratory is Google’s latest contribution to AI, wherein users can code in Python using a Chrome browser in a Jupyter-like environment. In this article I have shared a method, and code, to create a simple binary text classifier using Scikit Learn within Google CoLaboratory environment.
In this post, I share more technical details on how to build good data pipelines and highlight ETL best practices. Primarily, I will use Python, Airflow, and SQL for our discussion.
Does GDPR require Machine Learning algorithms to explain their output? Probably not, but experts disagree and there is enough ambiguity to keep lawyers busy.
This article gives a brief introduction about evolutionary algorithms (EAs) and describes genetic algorithm (GA) which is one of the simplest random-based EAs.
Take part in the Financial Entity Challenges. Sign up to participate, download the data, submit your solution, and come talk about your work at the ACM DSMM 2018 Workshop.
This June 18-19, RE-WORK will be returning to San Francisco to host the Deep Learning for Robotics Summit and the AI in Industrial Automation Summit. Save 20% with the code KDNUGGETS
The Data Science Learnathon is coming to the US, coast to coast. Learn how to use open source, GUI driven KNIME Analytics Platform. We’ll provide datasets, jump-start workflows, solutions, and of course data science experts. Sign-up now.
Analytics is becoming important part of maintenance, with applications to analyzing part failures, using failure distributions to simulate product life, and determining the root cause of failures. We provide an overview of predictive maintenance, its usage and key issues to be considered.
I now believe that there is an art, or craftsmanship, to structuring machine learning work and none of the math heavy books I tended to binge on seem to mention this.
Udemy St Patrick's Day $11.99 sale on top courses from leading instructors and learn Machine Learning, Data Science, Python, Azure Machine Learning, and more.
John Elder, Founder & Chair, Elder Research is confirmed to deliver a keynote address at the Predictive Analytics World Mega-Event, taking place in Las Vegas on Jun 3-7, 2018.
Also: 5 Things to Know About Machine Learning; 18 Inspiring Women In AI, Big Data, Data Science, Machine Learning; Great Data Scientists Don't Just Think Outside the Box, They Redefine the Box; Is an AI /machine-driven world better than a human driven world?
Choropleth maps provides a very simple and easy way to understand visualizations of a measurement across different geographical areas, be it states or countries.
Never fear, workforce analytics is here. We've put together a dedicated track at the 2018 Mega-PAW event in Las Vegas, Jun 3-7, covering Workforce analytics (retaining & optimizing HR with analytics), benefiting your work in HR analytics and beyond.
Model Risk Management has recently become a very hot topic in regulatory and compliance-rich industries. Join DataRobot on Mar 29, 2018 for a webinar titled "Model Risk Management with Automated Machine Learning."
2018 conference will gather 1,000 experts and thought leaders in industry, government, and academia, with over 150 sessions by leading universities and organizations. Register by March 12 to get early rates.
There are good reasons to want to use R for text processing, namely that we can do it, and that we can fit it in with the rest of our analyses. Furthermore, there is a lot of very active development going on in the R text analysis community right now.
More than just BI, Looker is a modern data platform that can serve the data needs of an entire company, with a balance of self-service and governance with access to a single-source of truth.
The AI Conference returns to New York, Apr 28-May 2. No other conference delivers the depth and breadth in technical content combined with an applied industry focus. Save an extra 20% on most passes with code PCKDNG.
For the 2018 international women's day, we profile 18 inspiring women who lead the field in AI, Analytics, Big Data , Data science, and Machine Learning areas.
Mobile platforms are set to benefit from Deep Learning this year, with significant improvements in privacy, offline functionality and much more. But which Android phone should you purchase to maximise these benefits?
The best data scientists have strong imaginative skills for not just “thinking outside the box” – but actually redefining the box – in trying to find variables and metrics that might be better predictors of performance.
This post will point out 5 thing to know about machine learning, 5 things which you may not know, may not have been aware of, or may have once known and now forgotten.
Also: Introduction to Functional Programming in #Python; 5 Quick and Easy #DataVisualization in #Python with Code; Predicting the 2018 #Oscar Winners with #MachineLearning; #Keras implementations of Generative Adversarial Networks
The agenda is live for Predictive Analytics World for Healthcare, Jun 3-7 in Las Vegas, and the conference schedule features five information packed days filled with insightful keynote presentations, interactive workshops, actionable seminars, and great networking opportunities.
Accelerate AI (X AI) brings business professionals, management and thought leaders together with executive speakers and AI experts to learn one of the most important skills necessary for future success, artificial intelligence. Save 60% with code KDNUGGETS.
On the positive side of AI we have a prospect of self-driving cars, and other benefits, and thru education humans can evolve and improve. The risks include loss of jobs, growing inequality, dealing with superintelligence.
Are you a Data Scientist looking for a Job? Are you a Recruiter looking for a Data Scientist? If you answered yes or NO to this questions you need to read this.
Also: Top 20 Python AI and Machine Learning Open Source Projects, A Tour of The Top 10 Algorithms for Machine Learning Newbies; 8 Neural Network Architectures Machine Learning Researchers Need to Learn.
Predictive Analytics World for Financial is heading to Las Vegas, NV on Jun 3-7, 2018 and we're excited to announce the speaker line-up for the conference program.
The Technically Speaking webcasts provides real-word case studies that deliver key insights on overcoming the challenges with your data collection, preparation, and analysis.
Major technological advances are providing opportunities for new business models, based on blockchain, which will see an increase in the number of connected devices in our day-to-day lives.
The question has probably come up of whether it’s ever okay to offer your data-related knowledge to people or organizations for free. Does taking that approach ever benefit you?
The 5th AI+Blockchain NEXTCon brings 50+ tech lead speakers from Microsoft, Google, Facebook, LinkedIn, Uber, other leading firms to share best practices and solutions in machine learning, deep learning, NLP, Data science, Blockchain and more. Save 30% by Mar 9 with code KDNUGGET100.
Enhance your skill set with a data analytics degree — 100% online. Check out the 30-credit Master's in Data Analytics, delivered through Penn State World Campus.
Time series forecasting is an easy to use, low-cost solution that can provide powerful insights. This post will walk through introduction to three fundamental steps of building a quality model.
Also: Gainers and Losers in Gartner 2018 Magic Quadrant for Data Science and Machine Learning Platforms; How data science can improve retail; Data Science in Fashion; Data Science for Javascript Developers
I hope to clarify some processes to attack DL problems and also discuss why it performs so well in some areas such as Natural Language Processing (NLP), image recognition, and machine-translation while failing at others.
Coming soon: Strata San Jose, IBM Think Las Vegas, KNIME Spring Summit Berlin, Predictive Analytics Innovation London, ICDIS Texas, AnacondaCON Austin, and many more.
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.
The goal of this tutorial is to open the door to data science programming using Javascript. This tutorial is intended for Javascript programmers without any data science experience.
Get real performance results and download the free Intel Distribution for Python that includes everything you need for blazing-fast computing, analytics, machine learning, and more.
There are many different ways to do image recognition. Google recently released a new Tensorflow Object Detection API to give computer vision everywhere a boost.
There are many wonderful things about data science. It’s extreme breadth is not one of them. The title of data scientist means something different at every company
We may be well into 2018, but here are a set of tech trends for looking forward, along with a set of 4 systems that manifested how inappropriate, inaccurate or outright broken they are in 2017.
Top 20 Deep Learning Papers, 2018 Edition
A “Weird” Introduction to Deep Learning
Exploring DeepFakes
Text Data Preprocessing: A Walkthrough in Python
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