All (108) | Courses, Education (11) | Meetings (8) | News, Features (11) | Opinions, Interviews (31) | Top Stories, Tweets (11) | Tutorials, Overviews (30) | Webcasts & Webinars (6)
- Top KDnuggets tweets, Jan 24-30: Top 10 Algorithms for Machine Learning Newbies; Want to Become a Data Scientist? Try Feynman Technique - Jan 31, 2018.
Also: Chronological List of AI Books To Read - from Goedel, Escher, Bach ... ; Aspiring Data Scientists! Start to learn Statistics with these 6 books.
- 2018 Data Science Salary Survey Report - Jan 31, 2018.
Throughout 2017, we conducted an online salary survey open to a range of data science professionals in order to capture data to help us better understand the market.
- MS in Health Informatics/Data Analytics from USF, San Francisco - Jan 30, 2018.
Learn about how USF MS in Health Informatics program can help you join our rapidly evolving healthcare industry.
- How to Make Life Easy for a Newly Hired Data Scientist - Jan 30, 2018.
In this post, I am going to describe the life of a newly hired data scientist. The use case is that the data scientist is given a project where he needs to build an online learning model.
- Automated Text Classification Using Machine Learning - Jan 30, 2018.
In this post, we talk about the technology, applications, customization, and segmentation related to our automated text classification API.
- My Journey into Deep Learning - Jan 30, 2018.
In this post I’ll share how I’ve been studying Deep Learning and using it to solve data science problems. It’s an informal post but with interesting content (I hope).
- Data Structures Related to Machine Learning Algorithms - Jan 30, 2018.
If you want to solve some real-world problems and design a cool product or algorithm, then having machine learning skills is not enough. You would need good working knowledge of data structures.
- Top Stories, Jan 22-28: Comparing Machine Learning as a Service; A Beginners Guide to Data Engineering – Part I - Jan 29, 2018.
Also: How To Grow As A Data Scientist; Training and Visualising Word Vectors; Using Genetic Algorithm for Optimizing RNNs; Top 10 Machine Learning Algorithms for Beginners; Comparing Machine Learning as a Service
- Webinar: AI, Machine Learning and Chatbots Improving Insurance Profitability & CX, Feb 15 - Jan 29, 2018.
Join Insurance Nexus as we talk to MetLife, Chubb and Nationwide about how to prioritize investments and internal resources. Learn which innovations will have the biggest impact on customer experience and improved profitability.
- Data Scientist – best job in America, 3 years in a row - Jan 29, 2018.
For the third year in a row, Data Scientist was ranked as the no. 1 job in America by Glassdoor.
- Error Analysis to your Rescue – Lessons from Andrew Ng, part 3 - Jan 29, 2018.
The last entry in a series of posts about Andrew Ng's lessons on strategies to follow when fixing errors in your algorithm
- Using AutoML to Generate Machine Learning Pipelines with TPOT - Jan 29, 2018.
This post will take a different approach to constructing pipelines. Certainly the title gives away this difference: instead of hand-crafting pipelines and hyperparameter optimization, and performing model selection ourselves, we will instead automate these processes.
- KDD 2018 Call for Research, Applied Data Science Papers - Jan 27, 2018.
KDD-2018 invites submission of papers describing innovative research on all aspects of data science, and of applied papers describing designs and implementations for practical tasks in data science. Submissions due Feb 11.
- MS in Data Analytics and Visualization, Online or NYC - Jan 26, 2018.
Whether you need a career boost or are looking to train employees, our flexible Data Analytics and Visualization program will help train effective, nimble leaders in data analytics.
- Bio-acoustic Structure, a NIMBioS Investigative Workshop, needs Data Scientists – Call for Applications - Jan 26, 2018.
This workshop will bring together experts in bio-acoustics with mathematicians and computer scientists with expertise in classification, clustering, and information theory to develop a unified approach. Apply by March 5.
- Data Science vs Addiction: Estimating Opioid Abuse by Location - Jan 26, 2018.
Data science can help find the optimal locations for drug treatment facilities, even in the face of major data challenges.
- 5 Key Data Science Job Market Trends - Jan 26, 2018.
As a data scientist — or someone interested in the field — you know the industry is constantly evolving. If you want to remain competitive, you need to keep up with popular trends.
- Using Deep Learning to Solve Real World Problems - Jan 25, 2018.
Deep learning offers every company with large data new techniques to solve complex analytical problems. Read this ebook to learn more.
- Exclusive Interview: Doug Laney on Big Data and Infonomics - Jan 25, 2018.
We discuss 3Vs of Big Data; Infonomics and many aspects of monetizing information including promising analytics methods, successful companies, main challenges; Information marketplaces and why data ownership concept is misguided, and more.
- Four Big Data Trends for 2018 - Jan 25, 2018.
Curious about the future of Big Data and AI? Here’s what the trends have it in 2018 for innovations.
- A Beginner’s Guide to Data Engineering – Part I - Jan 25, 2018.
Data Engineering: The Close Cousin of Data Science.
- GraphDB for DevOps – Live Online training from Ontotext - Jan 25, 2018.
This live online training is geared towards one single goal – to prepare developers and operations specialists who need to interact with GraphDB in their daily routine. For a limited time get 20% Early Bird discount.
- How To Grow As A Data Scientist - Jan 25, 2018.
In order for a data scientist to grow, they need to be challenged beyond the technical aspects of their jobs. They need to question their data sources, be concise in their insights, know their business and help guide their leaders.
- Top KDnuggets tweets, Nov 17 – 23: 10 Free #MachineLearning and #DataScience Books; Fundamental #Python #DataScience Libraries: A Cheatsheet #pandas - Jan 24, 2018.
Also: Advice For New and Junior #DataScientists; 5 EBooks to Read Before Getting into A #MachineLearning Career; #Blockchain or Bullshit; 30 Essential #DataScience, #MachineLearning & #DeepLearning Cheat Sheets
- Kogentix Automated Machine Learning Platform - Jan 24, 2018.
Kogentix Automated Machine Learning Platform is the only solution we have seen that runs natively on Spark and includes all of the elements required to build and run a machine learning application.
- Operational Best Practices for Enterprise Data Science - Jan 24, 2018.
Join Team Anaconda for a live webinar, Jan 30, 2pm CT, as we tackle the four main concerns we hear from our customers and show you best practices for managing enterprise data science: scalability, security, integration, and governance.
- Want to Become a Data Scientist? Try Feynman Technique - Jan 24, 2018.
Get over the impostor syndrome by developing a strong understanding about the various Data Science topics using the Feynman Technique
- Managing Machine Learning Workflows with Scikit-learn Pipelines Part 3: Multiple Models, Pipelines, and Grid Searches - Jan 24, 2018.
In this post, we will be using grid search to optimize models built from a number of different types estimators, which we will then compare and properly evaluate the best hyperparameters that each model has to offer.
- AI and Sentiment Analysis to help you move ahead of the competition - Jan 23, 2018.
A series of stimulating conferences on AI and Sentiment Analysis in Hong Kong, Bangalore and London. Use code KDHK20 to receive 20% discount on any of these events.
- Graduate programs in Data Analytics – 100% online - Jan 23, 2018.
Take advantage of this huge opportunity and enhance your skill set with a 30-credit Master's in Data Analytics degree from Penn State World Campus, offered entirely online.
- Machine Learning Model Metrics - Jan 23, 2018.
In this article we explore how to calculate machine learning model metrics, using the example of fraud detection. We'll see lots of different ways that we can try to understand just how good our learned model is.
- Using Excel with Pandas - Jan 23, 2018.
In this tutorial, we are going to show you how to work with Excel files in pandas, covering computer setup, reading in data from Excel files into pandas, data exploration in pandas, and more.
- Training and Visualising Word Vectors - Jan 23, 2018.
In this tutorial I want to show how you can implement a skip gram model in tensorflow to generate word vectors for any text you are working with and then use tensorboard to visualize them.
- Data Science in 30 minutes, Artificial General Intelligence, and Answers to your Questions - Jan 22, 2018.
I recently was on a "Data Science in 30 minutes webcast", but there were interesting ideas and questions we did not have time to cover adequately. Here is a summary.
- Predictive Analytics World Agendas Are Live—PAW Business & PAW Financial, June in Vegas - Jan 22, 2018.
The agenda is live for Predictive Analytics World for Business and Predictive Analytics World for Financial Services Las Vegas — June 3-7, 2018 at Caesars Palace — and we wanted to make sure that you are the first to know.
- Change Your Career in 2018: $100 off Dataquest’s Annual Premium Plan - Jan 22, 2018.
To celebrate the new year, Dataquest is offering 50% off their Premium plan for a limited time when you subscribe to yearly. Change your career now!
- Discover the new MSc in Digital Marketing & Data Science - Jan 22, 2018.
The MSc in Digital Marketing & Data Science is a 16-month programme designed to grow a new generation of leading marketing specialists – digital savvy professionals. Get 10% tuition fee waiver by submitting online application by Feb 1, 2018.
- Deep Learning in H2O using R - Jan 22, 2018.
This article is about implementing Deep Learning (DL) using the H2O package in R. We start with a background on DL, followed by some features of H2O's DL framework, followed by an implementation using R.
- Comparing Machine Learning as a Service: Amazon, Microsoft Azure, Google Cloud AI - Jan 22, 2018.
A complete and unbiased comparison of the three most common Cloud Technologies for Machine Learning as a Service.
- Using Genetic Algorithm for Optimizing Recurrent Neural Networks - Jan 22, 2018.
In this tutorial, we will see how to apply a Genetic Algorithm (GA) for finding an optimal window size and a number of units in Long Short-Term Memory (LSTM) based Recurrent Neural Network (RNN).
- Top Stories, Jan 15-21: The Value of Semi-Supervised Machine Learning; A Day in the Life of an AI Developer - Jan 22, 2018.
Also: Managing Machine Learning Workflows with Scikit-learn Pipelines Part 2: Integrating Grid Search; Generative Adversarial Networks, an overview; Learning Curves for Machine Learning; Top 10 TED Talks for Data Scientists and Machine Learning Engineers
- Learn Data Science Without a Degree - Jan 19, 2018.
But how do you learn data science? Let’s take a look at some of the steps you can take to begin your journey into data science without needing a degree, including Springboard’s Data Science Career Track.
- Plot2txt for quantitative image analysis - Jan 19, 2018.
Plot2txt converts images into text and other representations, helping create semi-structured data from binary, using a combination of machine learning and other algorithms.
- Managing Machine Learning Workflows with Scikit-learn Pipelines Part 2: Integrating Grid Search - Jan 19, 2018.
Another simple yet powerful technique we can pair with pipelines to improve performance is grid search, which attempts to optimize model hyperparameter combinations.
- Are you monitoring your machine learning systems? - Jan 18, 2018.
How are you monitoring your Python applications? Take the short survey - the results will be published on KDnuggets and you will get all the details.
- Online MSc in Applied Data Science, Big Data – part-time, small, private - Jan 18, 2018.
DSTI mission is simple: training executive students to become ready-to-go Data Scientists and Big Data Analysts. Check our small private online course programme.
- Visual Aesthetics: Judging photo quality using AI techniques - Jan 18, 2018.
We built a deep learning system that can automatically analyze and score an image for aesthetic quality with high accuracy. Check the demo and see your photo measures up!
- Propensity Score Matching in R - Jan 18, 2018.
Propensity scores are an alternative method to estimate the effect of receiving treatment when random assignment of treatments to subjects is not feasible.
- Gradient Boosting in TensorFlow vs XGBoost - Jan 18, 2018.
For many Kaggle-style data mining problems, XGBoost has been the go-to solution since its release in 2016. It's probably as close to an out-of-the-box machine learning algorithm as you can get today.
- Top KDnuggets tweets, Jan 10-16: The Art of Learning #DataScience; Gradient Boosting in #TensorFlow vs XGBoost - Jan 17, 2018.
Also Japanese scientists just used #AI #DeepLearning to read minds and it's amazing; Using #DeepLearning to Solve Real World Problems.
- Webinar: Minimizing Model Risk with Automated Machine Learning, Jan 31 - Jan 17, 2018.
See how banks can use Automated Machine Learning to gain a competitive advantage, while quickly aligning their business operation to regulatory requirements.
- The Value of Semi-Supervised Machine Learning - Jan 17, 2018.
This post shows you how to label hundreds of thousands of images in an afternoon. You can use the same approach whether you are labeling images or labeling traditional tabular data (e.g, identifying cyber security atacks or potential part failures).
- Learning Curves for Machine Learning - Jan 17, 2018.
But how do we diagnose bias and variance in the first place? And what actions should we take once we've detected something? In this post, we'll learn how to answer both these questions using learning curves.
- The LION WAY, v. 3.0: Machine Learning plus Intelligent Optimization – Free Download - Jan 16, 2018.
This newly revised book presents two topics which are in most cases separated: machine learning (the design of flexible models from data) and intelligent optimization (the automated creation and selection of improving solutions). Free download!
- Mining Data for Efficient, Personalized Claims: Co-operators, Hiscox and American National - Jan 16, 2018.
How can insurance carriers gather and integrate data, and more importantly, effectively generate actionable insights to turn data into value? Get a whitepaper with best practices, including data collection, analytics, and value-add services.
- Northwestern’s MS in Data Science - Jan 16, 2018.
Northwestern’s MASTER OF SCIENCE IN DATA SCIENCE is a fully online, part-time program that helps students build essential analysis and leadership skills for today's data-driven world.
- Topological Data Analysis for Data Professionals: Beyond Ayasdi - Jan 16, 2018.
We review recent developments and tools in topological data analysis, including applications of persistent homology to psychometrics and a recent extension of piecewise regression, called Morse-Smale regression.
- Governance in Data Science - Jan 16, 2018.
Governance roles for data science and analytics teams are becoming more common... One of the key functions of this role is to perform analysis and validation of data sets in order to build confidence in the underlying data sets.
- A Day in the Life of an AI Developer - Jan 16, 2018.
This is the narrative of a typical AI Sunday, where I decided to look at building a sequence to sequence (seq2seq) model based chatbot using some already available sample code and data from the Cornell movie database.
- Generative Adversarial Networks, an overview - Jan 15, 2018.
In this article, we’ll explain GANs by applying them to the task of generating images. One of the few successful techniques in unsupervised machine learning, and are quickly revolutionizing our ability to perform generative tasks.
- Looker Data Tour: London, Feb 13 - Jan 15, 2018.
Register for Looker #JOINtheTour first stop - #London! Experience a day full of inspiring keynotes, helpful #tech sessions, and networking with lots of #datadriven folks.
- Pick Up New Skills – 8 Full-Day Workshops at Predictive Analytics World this June in Vegas - Jan 15, 2018.
In 2018, there will be only one PAW. Pick Up New Skills at Predictive Analytics World Workshops, Las Vegas, June 2018.
- Top Stories, Jan 8-14: Top 10 TED Talks for Data Scientists and Machine Learning Engineers; The Art of Learning Data Science - Jan 15, 2018.
Also: How Docker Can Help You Become A More Effective Data Scientist; Regularization in Machine Learning; Democratizing Artificial Intelligence, Deep Learning, Machine Learning with Dell EMC Ready Solutions; Quantum Machine Learning: An Overview
- Is Learning Rate Useful in Artificial Neural Networks? - Jan 15, 2018.
This article will help you understand why we need the learning rate and whether it is useful or not for training an artificial neural network. Using a very simple Python code for a single layer perceptron, the learning rate value will get changed to catch its idea.
- Local AI Inferencing Will Become Standard In Edge Applications In 2018 - Jan 12, 2018.
Edge-based inferencing will become a foundation of all AI-infused applications in the Internet of Things and People and the majority of new IoT&P application-development projects will involve building the AI-driven smarts for deployment to edge devices for various levels of local sensor-driven inferencing.
- Strata Data Conference San Jose – early price ends Jan 19 - Jan 12, 2018.
Strata Data Conference is where top data scientists, analysts, engineers, and executives converge to shape the future of business and technology. Rates go up Jan 19 - save extra 20% with code KDNU.
- Elasticsearch for Dummies - Jan 12, 2018.
In this blog, you’ll get to know the basics of Elasticsearch, its advantages, how to install it and indexing the documents using Elasticsearch.
- A Primer on Web Scraping in R - Jan 12, 2018.
If you are a data scientist who wants to capture data from such web pages then you wouldn’t want to be the one to open all these pages manually and scrape the web pages one by one. To push away the boundaries limiting data scientists from accessing such data from web pages, there are packages available in R.
- OpenMinTED Open Tender Phase II Funding opportunity for text and data mining developers - Jan 11, 2018.
OpenMinTED invites researchers, service providers and SMEs to submit proposals related to the development and integration of existing text mining/NLP applications or software components. Apply by Jan 26, 2018.
- AI and Deep Learning in Healthcare – save with code KDnuggets - Jan 11, 2018.
This year, RE-WORK will be continuing the Global Healthcare Series, focusing on the AI and deep learning tools and techniques set to revolutionise healthcare applications, medicine & diagnostics. Save an additional 20% on already discounted passes with the code: KDNUGGETS
- 5 things that will be important in data science in 2018 - Jan 11, 2018.
What’s data science going to look like in 2018? How are job roles in the field going to change? Will AI find new ways to capture the public imagination? Learn more from Packt $5 books - on sale till Jan 16.
- Beyond Word2Vec Usage For Only Words - Jan 11, 2018.
A good example on how to use word2vec in order to get recommendations fast and efficiently.
- Democratizing Artificial Intelligence, Deep Learning, Machine Learning with Dell EMC Ready Solutions - Jan 11, 2018.
Democratization is defined as the action/development of making something accessible to everyone, to the “common masses.” AI | ML | DL technology stacks are complicated systems to tune and maintain, expertise is limited, and one minimal change of the stack can lead to failure.
- How Not To Lie With Statistics - Jan 11, 2018.
Darrell Huff's classic How to Lie with Statistics is perhaps more relevant than ever. In this short article, I revisit this theme from some different angles.
- Top KDnuggets tweets, Jan 3-9: A collection of Jupyter notebooks NumPy, Pandas, matplotlib, basic #Python #MachineLearning - Jan 10, 2018.
Artificial General Intelligence (AGI) in less than 50 years; Top KDnuggets tweets: 10 Free Must-Read Books for #MachineLearning and #DataScience; The Art of Learning #DataScience; Supercharging Visualization with Apache Arrow; Docker for #DataScience
- Top 10 TED Talks for Data Scientists and Machine Learning Engineers - Jan 10, 2018.
A comprehensive and diverse compilation of TED talks to understand the big picture of AI and Machine Learning.
- Regularization in Machine Learning - Jan 10, 2018.
Regularization is a technique that helps to avoid overfitting and also make a predictive model more understandable.
- How Docker Can Help You Become A More Effective Data Scientist - Jan 10, 2018.
I wrote this quick primer so you don’t have to parse all the information out there and instead can learn the things you need to know to quickly get started.
- Top December Stories: Computer Vision by Andrew Ng – 11 Lessons Learned; Top Data Science and Machine Learning Methods Used in 2017 - Jan 9, 2018.
Also: How Much Mathematics Does an IT Engineer Need to Learn to Get Into Data Science? Data Science, Machine Learning: Main Developments in 2017 and Key Trends in 2018.
- Where Will Data Science and Marketing Analytics Take You in 2018? - Jan 9, 2018.
MADS Can Help You Achieve Your 2018 Goals in San Francisco, April 11-13, 2018. Hear from speakers like DJ Patil, Former U.S. Chief Data Scientist, as he reveals the secrets to navigating the digital transformation. Save 20% with VIP Code MADS18KDN.
- Driverless AI: Fast, Accurate, Interpretable AI - Jan 9, 2018.
H2O.ai recently launched Driverless AI, which speeds up data science workflows by automating feature engineering, model tuning, ensembling, and model deployment.
- The Art of Learning Data Science - Jan 9, 2018.
A beginner’s account of getting into comfort zone of learning Data Science.
- Becoming a Data Scientist - Jan 9, 2018.
This article contains a lot of links to resources that I think are very helpful in getting you started to "think like a data scientist" which in my opinion is the most important step of the transition. I hope that you find this useful.
- Training Sets, Test Sets, and 10-fold Cross-validation - Jan 9, 2018.
More generally, in evaluating any data mining algorithm, if our test set is a subset of our training data the results will be optimistic and often overly optimistic. So that doesn’t seem like a great idea.
- After the “Meltdown,” How Can You Protect Your Database? - Jan 8, 2018.
- New E-learning course: Profit-driven Business Analytics - Jan 8, 2018.
The e-learning course on profit-driven business analytics presents a toolbox of advanced analytical approaches that support subsequent cost-optimal decision making.
- Custom Optimizer in TensorFlow - Jan 8, 2018.
How to customize the optimizers to speed-up and improve the process of finding a (local) minimum of the loss function using TensorFlow.
- Introductory Data Concepts: Fantastic Video Tutorials from Ronald van Loon - Jan 8, 2018.
Check out these introductory data videos from noted expert and influencer Ronald van Loon.
- Top Stories, Jan 1-7: Docker for Data Science; Quantum Machine Learning: An Overview - Jan 8, 2018.
Also: Computer Vision by Andrew Ng – 11 Lessons Learned; How to build a Successful Advanced Analytics Department; Docker for Data Science; Top 10 Machine Learning Algorithms for Beginners
- Cartoon: AI at Home: How Far Can A Smart Device Go? - Jan 6, 2018.
New KDnuggets cartoon looks at AI at Home technology and considers how a novel way how a smart device can help its owner to lose weight.
- Top Data Science, Machine Learning Courses from Udemy - Jan 5, 2018.
Enjoy the New Year sale on top courses from leading instructors and learn Machine Learning, Data Science, Python, Azure Machine Learning, and more.
- Artificial General Intelligence (AGI) in less than 50 years, say KDnuggets readers - Jan 5, 2018.
Artificial General Intelligence (AGI) will likely be achieved in less than 50 years, according to latest KDnuggets Poll. The median estimate from all regions was 21-50 years, except in Asia where AGI is expected in 11-20 years.
- Quantum Machine Learning: An Overview - Jan 5, 2018.
Quantum Machine Learning (Quantum ML) is the interdisciplinary area combining Quantum Physics and Machine Learning(ML). It is a symbiotic association- leveraging the power of Quantum Computing to produce quantum versions of ML algorithms, and applying classical ML algorithms to analyze quantum systems. Read this article for an introduction to Quantum ML.
- Supercharging Visualization with Apache Arrow - Jan 5, 2018.
Interactive visualization of large datasets on the web has traditionally been impractical. Apache Arrow provides a new way to exchange and visualize data at unprecedented speed and scale.
- The Convergence of AI and Blockchain: What’s the deal? - Jan 5, 2018.
This article wants to give a flavor of the potentialities realized at the intersection of AI and Blockchain and discuss standard definitions, challenges, and benefits of this alliance, as well as about some interesting player in this space.
- How to build a Successful Advanced Analytics Department - Jan 4, 2018.
This article presents our opinions and suggestions on how an Advanced Analytics department should operate. We hope this will be useful for those who want to implement analytics work in their company, as well as for existing departments.
- 10 Tools to Help You Learn R - Jan 4, 2018.
There are several tools to help you grasp the foundational principles and more. The list below gives you an idea of what’s available and how much it costs.
- Top KDnuggets tweets, Dec 27 – Jan 02: 10 Free Must-Read Books for #MachineLearning and #DataScience - Jan 3, 2018.
Also #TensorFlow: A proposal of good practices for files, folders and models; Creating REST API for #TensorFlow models; The Most Popular Language For #MachineLearning and #DataScience Is ...
- Top Stories, Dec 18-31: How Much Mathematics Does an IT Engineer Need to Learn to Get Into Data Science?; Computer Vision by Andrew Ng – 11 Lessons Learned - Jan 3, 2018.
Also: 70 Amazing Free Data Sources You Should Know; Industry Predictions: Main AI, Big Data, Data Science Developments in 2017 and Trends for 2018; Can I Become a Data Scientist: Research into 1,001 Data Scientist Profiles; Yet Another Day in the Life of a Data Scientist
- Webcasts: Finding analytic solutions to real problems - Jan 3, 2018.
The Technically Speaking webcast series provides real-word case studies with key insights on overcoming the challenges in data collection, preparation, and analysis - find the webcast that fits your current challenge.
- Enhancing Anti-Money Laundering Programs with Automated Machine Learning, Jan 11 Webinar - Jan 3, 2018.
In this webinar, Jan 11, DataRobot will show how automated machine learning can be used to reduce false positive rates, thereby improving the efficiency of AML transaction monitoring and reducing costs.
- Data Science in 30 Minutes: A Conversation with Gregory Piatetsky-Shapiro, President of KDnuggets - Jan 3, 2018.
KDnuggets founder, Gregory Piatetsky-Shapiro, joins Michael Li, CEO and founder of The Data Incubator, Jan 11 at 2:30 pm PT/ 5:30 pm ET for their monthly webinar series, Data Science in 30 Minutes. Gregory will discuss his career, from AI to Data Mining to KDD to Data Science and back to AI, and examine current trends in the field.
- How Nonprofits Can Benefit from the Power of Data Science - Jan 3, 2018.
Nonprofits can use analytics to boost their fundraising efforts, measure and monitor the impact of their activities, build predictive models, optimize allocation of funds, and more
- Back to the Future: 2018 Big Data and Data Science Prognostications - Jan 3, 2018.
It’s really hard to find predictions about the future made in the 1950’s. I decided to review the most popular sci-fi movies from 1950’s, and provide my perspective as to what these movies might tell us about 2018.
- Upcoming Meetings in AI, Analytics, Big Data, Data Science, Deep Learning, Machine Learning: January and Beyond - Jan 2, 2018.
Coming soon: Deep Learning Summit San Francisco, Data Science Salon Miami, TDWI Las Vegas, BI + Analytics Conference Huntington Beach, Applied AI Summit London, Strata San Jose, and more.
- Everything Changes: A Human Perspective on Digitization - Jan 2, 2018.
An insightful, thought-provoking article on digital disruption and evolution of technology.
- Docker for Data Science - Jan 2, 2018.
Coming from a statistics background I used to care very little about how to install software and would occasionally spend a few days trying to resolve system configuration issues. Enter the god-send Docker almighty.
- Why understanding of truth is important in Data Science? - Jan 1, 2018.
Data Science can be used to discover correlations (What phenomena occurred) but cannot be used to establish causality (Why the phenomena occurred).