- The Data Science Project Playbook - Mar 1, 2017.
Keep your development team from getting mired in high-complexity, low-return projects by following this practical playbook.
- Getting Real World Results From Agile Data Science Teams - Feb 10, 2017.
In this post, I’ll look at the practical ingredients of managing agile data science. By using agile data science methods, we help data teams do fast and directed work, and manage the inherent uncertainty of data science and application development.
- Laying the Foundation for a Data Team - Dec 28, 2016.
Admittedly, there is a lot more to building a successful data team, and we would be lying if we pretended we have it all figured out. But hopefully focusing on the elements in this post is a good start.
- Supercharge Your Data Science Team, Dec 21 Webinar - Dec 20, 2016.
On December 21st, Continuum Analytics CTO Peter Wang will share how you can supercharge your Data Science team by simplifying the building process for even the most complicated dashboards and display streaming data in real time.
- Tips for Beginner Machine Learning/Data Scientists Feeling Overwhelmed - Nov 25, 2016.
Sebastian Raschka weighs in on how to battle stress as a beginner in the data science world. His insight is to-the-point, so reading it should be a stress-free endeavour.
- Data Avengers… Assemble! - Nov 19, 2016.
The Avengers are perfectly capable of defending the Earth from our worst enemies. But are they up to the task of taking care of our data? Read this terribly punny "opinion" piece to find out.
- Reasons Why Data Projects Fail - Nov 10, 2016.
Many companies seem to go through a pattern of hiring a data science team only for the entire team to quit or be fired around 12 months later. Why is the failure rate so high?
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- Big Data Science: Expectation vs. Reality - Oct 27, 2016.
The path to success and happiness of the data science team working with big data project is not always clear from the beginning. It depends on maturity of underlying platform, their cross skills and devops process around their day-to-day operations.
- How to Get Stuff Done at a Data Startup - Oct 13, 2016.
This post is a followup to how to structure data science teams, with a focus on how we get stuff done. The same principles we follow can be applied at your data startup or data science team.
- How to Structure Your Team When Building a Data Startup - Oct 1, 2016.
Data Startup in mind? Need to structure different teams? Here are guidelines for structuring Data Team, Crawl Development Team, Data Infrastructure Team, and more.
- The Core of Data Science - Aug 1, 2016.
This post provides a simplifying framework, an ontology for Machine Learning and some important developments in dynamical machine learning. From first hand Data Science product experience, the author suggests how best to execute Data Science projects.
- KDnuggets™ News 16:n21, Jun 15: What Big Data, Data Science tools go together? Oppys for Machine Learning Startups - Jun 15, 2016.
What Big Data, Data Science, Deep Learning software goes together? Opportunities for Machine Learning Startups; Top NoSQL Database Engines; How Do You Identify the Right Data Scientist for Your Team?
- How Do You Identify the Right Data Scientist for Your Team? - Jun 8, 2016.
Have you been trying to answer the question of what type of a data scientist would be the best fit for your team? Is there a single all-encompassing answer or does it vary based on the client objectives? Read on for some insight.
- The Benefits of Decentralizing Analytics Talent - Jun 4, 2016.
Over the next several years data will be served in a variety of ways, greater innovation will come from companies that look to share raw data. Here we talk about, democratizing the data which requires a different philosophy to allow all business functions to participate in analytics.
- Building effective “Citizens Data Scientist” teams - Apr 28, 2016.
The idea of citizen data scientists is being for more than a year, which suggests businesses to put the people from the business side in the work of exploring and analyzing data. Understand how you and your organisation can be benefitted by this.
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- Three Pitfalls to Avoid When Building Data Science Into Your Business - Apr 27, 2016.
An overview of pitfalls to avoid when building data science into your business, how to avoid them, and what to do instead.
- H2O World 2015 – Day 3 Highlights - Nov 20, 2015.
Highlights from talks delivered by machine learning experts from Fast Forward Labs, H20.ai, Kaiser and Macy's at H2O World held in Mountain View.
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- Three Essential Components of a Successful Data Science Team - Aug 10, 2015.
Finding unicorn is way to difficult, building the data science team looks more feasible. Find out the its components data engineer, machine learning expert and business analyst along with their responsibilities and ideal characteristics.
- Webinar On-Demand: Your First Hire in Predictive Analytics (Hint: it is not a Data Scientist) - Jul 28, 2015.
In a thriving analytic practice, the role of a data scientist is not defined by a person, but by a team. Within that team, several roles may be filled by one person-and several people may fulfill a given role.
- Analytics Outsourcing to India: Should or Shouldn’t? - Feb 5, 2015.
Outsourcing analytics talent to India will continue to grow as a trend as evidenced by the increasing number of Fortune 500 companies participating in the practice.
- KDnuggets talks to IBM: Data scientists: Hire an individual or team? - Feb 13, 2014.
KDnuggets recent poll about Data Science - Individual vs Team has caught attention of IBM. Listen to the podcast where I discuss the unexpected findings of this poll and other Data Science topics.
- KDnuggets 14:n02, Split on Data Science; Data Science in Python Tutorial - Jan 22, 2014.
Split on Data Science - Team vs Individual Approach, Data Science in Python - free tutorial, PASS Free Online Business Analytics Training - Feb 5, Confessions of a Dataholic, and more analytics/data mining news.