Mar
2015 Apr Opinions, Interviews, Reports
All (122) | Courses, Education (9) | Meetings (11) | News, Features (19) | Opinions, Interviews, Reports (44) | Publications (14) | Software (11) | Top Tweets (5) | Webcasts (9)
- Interview: Haile Owusu, Mashable on Riding the Wave of Viral Content
- Apr 29, 2015.
We discuss Mashable’s milestones, data-driven digital publishing, digital media tracking, viral prediction, and Mashable Velocity.
- Data Scientists Thoughts that Inspire
- Apr 29, 2015.
Inspirational thoughts from leading data scientists, including Yann LeCun, Erin Shellman, Daniel Tunkelang, Claudia Perlich, and Jake Porway. What inspires you?
- How to become a Data Scientist – brief answer
- Apr 28, 2015.
The most important steps to become a Data Scientist: learn Python, deep understanding of machine learning, try to be up-to-date. Check more details in the post.
- Interview: Mario Vinasco, Facebook on Advancing Marketing Analytics through Rigorous Experimentation
- Apr 27, 2015.
We discuss marketing analytics at Facebook, multi-channel performance assessment, success factors, lessons from Look Back feature, advice, and more.
- The Myth of Model Interpretability
- Apr 27, 2015.
Deep networks are widely regarded as black boxes. But are they truly uninterpretable in any way that logistic regression is not?
- New Hybrid Rare-Event Sampling Technique for Fraud Detection
- Apr 26, 2015.
Proposed hybrid sampling methodology may prove useful when building and validating machine learning models for applications where target event is rare, such as fraud detection.
- Interview: Emmanuel Letouzé, Data-Pop Alliance on Big Data for Development and Future Prospects
- Apr 25, 2015.
We discuss the field of Big Data for Development, current projects and future plans for Data-Pop Alliance, public participation opportunities, advice, and more.
- Interview: Emmanuel Letouzé, Data-Pop Alliance on Democratizing the Benefits of Big Data
- Apr 24, 2015.
We discuss the 3 Cs of Big Data, state of ethics in the field of Big Data, and how to ensure that the benefits of Big Data reach the masses.
- Big Data Bootcamp, Austin: Day 3 Highlights
- Apr 24, 2015.
Highlights from the presentations by Big Data and Analytics leaders/consultants on day 3 of Big Data Bootcamp in Austin.
- MapR on Open Data Platform: Why we declined
- Apr 24, 2015.
Why MapR declined to participate in the Open Data Platform? Our concerns include redundancy with Apache Software Foundation Governance, misdefined “core”, and lack of participation from Hadoop leaders.
- Big Data Bootcamp, Austin: Day 2 Highlights
- Apr 23, 2015.
Highlights from the presentations by Big Data and Analytics leaders/consultants on day 2 of Big Data Bootcamp in Austin.
- Interview: Emmanuel Letouzé, Data-Pop Alliance on the Role of Big Data in Economic Development
- Apr 23, 2015.
We discuss the emerging Big Data ecosystem, its key players, and the severe consequences of inadequate statistical capabilities across many African nations.
- Big Data Bootcamp, Austin: Day 1 Highlights
- Apr 22, 2015.
Highlights from the presentations by Big Data and Analytics leaders/consultants on day 1 of Big Data Bootcamp 2015 in Austin.
- Interview: Emmanuel Letouzé, Data-Pop Alliance on Big Data and Human Rights – A Complex Affair
- Apr 22, 2015.
We discuss the founding story of Data-Pop Alliance, the applications and implications of Big Data on Human Rights and the need for penetration of Data Literacy.
- Deep Learning to Fight Crime
- Apr 22, 2015.
We look at how using Deep Learning, Spark, and H2O Machine Learning platform can be used to analyze and predict crime in San Francisco and Chicago.
- Interview: Michael Li, Data Incubator on Bridging the Data Science Skills Gap between Academia and Industry
- Apr 21, 2015.
We discuss the response from hiring companies, recommendations for aspirants, retaining data science talent, advice, and more.
- Interview: Michael Li, Data Incubator on Data-driven Hiring for Data Scientists
- Apr 20, 2015.
We discuss the launch of the Data Incubator, its business model, why we need data-driven hiring, selection process for the incubator program and alumni feedback.
- PAW San Francisco 5 Min Recap – Predictive Analytics World
- Apr 20, 2015.
PAW San Francisco: 550+ Data Professionals, 85+ conference sessions, 4 conferences, Dean Abbott on 3-legged stool of good data, domain expertise, and advanced analytics, and more.
- Interview: Ksenija Draskovic, Verizon on Conquering Fear and Cherishing Creativity for Success in Data Science
- Apr 17, 2015.
We discuss career advice, motivation, key qualities sought in Data Science practitioners, and more.
- Data Science 101: Preventing Overfitting in Neural Networks
- Apr 17, 2015.
Overfitting is a major problem for Predictive Analytics and especially for Neural Networks. Here is an overview of key methods to avoid overfitting, including regularization (L2 and L1), Max norm constraints and Dropout.
- Interview: Ksenija Draskovic, Verizon on How to Not Get Lost in the Big Data Wilderness
- Apr 16, 2015.
We discuss recommendations for data-driven decision making, challenges and benefits of using unstructured data, managing expectations and key trends.
- Cloud Machine Learning Wars: Amazon vs IBM Watson vs Microsoft Azure
- Apr 16, 2015.
Amazon recently announced Amazon Machine Learning, a cloud machine learning solution for Amazon Web Services. Able to pull data effortlessly from RDS, S3 and Redshift, the product could pose a significant threat to Microsoft Azure ML and IBM Watson Analytics.
- Interview: Ksenija Draskovic, Verizon on Dissecting the Anatomy of Predictive Analytics Projects
- Apr 15, 2015.
We discuss Predictive Analytics use cases at Verizon Wireless, advantages of a unified data view, model selection and common causes of failure.
- Interview: Michael Lurye, Time Warner Cable on Key Lessons from Shifting to Hadoop
- Apr 14, 2015.
We discuss the key lessons from shifting to Hadoop, data management in today’s world, future of Data Science, advice and more.
- Interview: Michael Lurye, Time Warner Cable on Big Data and the Insatiable Demand for BI
- Apr 13, 2015.
We discuss EDM at Time Warner Cable, data sources, complementing legacy data warehouses with Big Data solutions, vendor selection and build vs. buy decision.
- Interview: Xia Wang, AstraZeneca on Big Data and the Promise of Effective Healthcare
- Apr 10, 2015.
We discuss challenges in analyzing text data, Big Data impact on translational bioinformatics, advice, desired skills in data scientists, and more.
- Algorithmia – How Marketplaces are Fostering Innovation?
- Apr 9, 2015.
We have a marketplace for almost everything – mobile apps, cabs, hotels, and what not. But, not for algorithms. Algorithmia takes up that challenge.
- Interview: Xia Wang, AstraZeneca on Unraveling Patient Treatment Journey by NLP on Clinical Notes
- Apr 9, 2015.
We discuss Analytics at AstraZeneca, prominent use cases, how NLP helped understanding patient treatment journey in diabetes, data sources, insights, and more.
- Inside Deep Learning: Computer Vision With Convolutional Neural Networks
- Apr 9, 2015.
Deep Learning-powered image recognition is now performing better than human vision on many tasks. We examine how human and computer vision extracts features from raw pixels, and explain how deep convolutional neural networks work so well.
- Machine Learning 201: Does Balancing Classes Improve Classifier Performance?
- Apr 9, 2015.
The author investigates if balancing classes improves performance for logistic regression, SVM, and Random Forests, and finds where it helps the performance and where it does not.
- Interview: Ravi Iyer, Ranker on Dealing with Inherent Bias in Crowdsourcing Data
- Apr 8, 2015.
We discuss the challenges of analyzing crowdsourcing data, tools and technologies, competitive landscape, advice, trends, and more.
- Predictive Analytics Innovation Summit, San Diego: Day 2 Highlights
- Apr 8, 2015.
Highlights from the presentations by Predictive Analytics leaders from eBay, LinkedIn and Facebook on day 2 of Predictive Analytics Innovation Summit 2015 in San Diego.
- Interview: Ravi Iyer, Ranker on Why Crowdsourcing Needs Data Science
- Apr 7, 2015.
We discuss the dynamics of Ranker crowdsourcing platform, key factors for effectiveness, role of data science in crowdsourcing, and more.
- Predictive Analytics Innovation Summit, San Diego: Day 1 Highlights
- Apr 7, 2015.
Highlights from the presentations by Predictive Analytics leaders from The Data Incubator, Tamr, Sony and Facebook on day 1 of Predictive Analytics Innovation Summit 2015 in San Diego.
- Be Smarter Than Your Devices: Learn About Big Data
- Apr 7, 2015.
If the Apple Watch rollout proves anything, it might be this: Going forward, we’ll all have to be as smart about data as our devices. Also, learn about the origins of "Big Data" term.
- Interview: Beth Diaz, Washington Post on How Dark Social is Shadowing Modern Analytics
- Apr 6, 2015.
We discuss recent events at Washington Post, growth initiatives, the growing pain of Dark Social, how to deal with it, audience analytics, advice and more.
- Big Data Developer Conference, Santa Clara: Day 3 Highlights
- Apr 3, 2015.
Highlights from the presentations/tutorials by Data Science leaders from VISA, Glassbeam, Unravel on day 3 of Big Data Developer Conference, Santa Clara.
- Interview: Alessandro Gagliardi, Glassdoor on the Fun and Boring Part of Data Scientist Job
- Apr 3, 2015.
We discuss interesting trends, motivation, different aspects of data scientist job, advice, and more.
- Big Data Developer Conference, Santa Clara: Day 2 Highlights
- Apr 2, 2015.
Highlights from the presentations/tutorials by Data Science leaders from Cloudera, LinkedIn, Intel, MapR, Locbit and others on day 2 of Big Data Developer Conference 2015.
- Hazy Forecast for Consumer Privacy in the Next Decade
- Apr 2, 2015.
Majority of experts felt that developing a privacy framework that would be both popular and functional was next to impossible in the near future. With time, privacy is likely tol become a class issue with consumers who have the money having the ability to secure their data better.
- Big Data Developer Conference, Santa Clara: Day 1 Highlights
- Apr 1, 2015.
Highlights from the presentations/tutorials by Data Science leaders from ElephantScale, SciSpike, Twitter and Informatica on day 1 of Big Data Developer Conference, Santa Clara
- Interview: Alessandro Gagliardi, Glassdoor on the Indispensable Skills for Data Scientists
- Apr 1, 2015.
We discuss Analytics at Glassdoor, important lessons, major factors affecting job satisfaction, challenges of working on Twitter Data, indispensable components of Data Science education.
- Gold Mine or Blind Alley? Functional Programming for Big Data & Machine Learning
- Apr 1, 2015.
Functional programming is touted as a solution for big data problems. Why is it advantageous? Why might it not be? And who is using it now?
- A Data Scientist Advice to Business Schools
- Apr 1, 2015.
To remain relevant business school graduates must learn to speak to Data Scientists, whose domain expertise is playing a vital role in an organization's ability to compete in today's market.
