- Setting Up Your Data Science & Machine Learning Capability in Python - Aug 4, 2020.
With the rich and dynamic ecosystem of Python continuing to be a leading programming language for data science and machine learning, establishing and maintaining a cost-effective development environment is crucial to your business impact. So, do you rent or buy? This overview considers the hidden and obvious factors involved in selecting and implementing your Python platform.
- Top 5 must-have Data Science skills for 2020 - Jan 8, 2020.
The standard job description for a Data Scientist has long highlighted skills in R, Python, SQL, and Machine Learning. With the field evolving, these core competencies are no longer enough to stay competitive in the job market.
- 7 Resources to Becoming a Data Engineer - Jan 7, 2020.
An estimated 8,650% growth of the volume of Data to 175 zetabytes from 2010 to 2025 has created an enormous need for Data Engineers to build an organization's big data platform to be fast, efficient and scalable.
- Alternative Cloud Hosted Data Science Environments - Dec 19, 2019.
Over the years new alternative providers have risen to provided a solitary data science environment hosted on the cloud for data scientist to analyze, host and share their work.
- The 4 Hottest Trends in Data Science for 2020 - Dec 9, 2019.
The field of Data Science is growing with new capabilities and reach into every industry. With digital transformations occurring in organizations around the world, 2019 included trends of more companies leveraging more data to make better decisions. Check out these next trends in Data Science expected to take off in 2020.
- Samsung Tech Day: Today’s Electronic Devices Seem Magical, But the Real Super-Power is in Silicon - Oct 23, 2019.
Samsung’s Tech Day event showcases processor and memory advances for 5G, AI, Cloud and Edge Computing, Automotive, IoT, and more.
- Using DC/OS to Accelerate Data Science in the Enterprise - Oct 15, 2019.
Follow this step-by-step tutorial using Tensorflow to setup a DC/OS Data Science Engine as a PaaS for enabling distributed multi-node, multi-GPU model training.
- Why do we need AWS SageMaker? - Jun 26, 2019.
Today, there are several platforms available in the industry that aid software developers, data scientists as well as a layman in developing and deploying machine learning models within no time.
- Understanding Cloud Data Services - Jun 24, 2019.
Ready to move your systems to a cloud vendor or just learning more about big data services? This overview will help you understand big data system architectures, components, and offerings with an end-to-end taxonomy of what is available from the big three cloud providers.
- Easy Way to Scrape Data from Website By Yourself - Apr 22, 2019.
Introducing Octoparse, a simple cloud-based website data scrapper that will let you extract any web data in real-time and coding is not needed.
- 8 Reasons Why You Should Get a Microsoft Azure Certification - Mar 18, 2019.
With huge and growing popularity of Microsoft Azure, getting that certification will advance your career. Consider these 8 reasons for taking an Azure certification course
- Best Deals in Deep Learning Cloud Providers: From CPU to GPU to TPU - Nov 15, 2018.
A detailed comparison of the best places to train your deep learning model for the lowest cost and hassle, including AWS, Google, Paperspace, vast.ai, and more.
- Top 3 Trends in Deep Learning - Oct 3, 2018.
We investigate the intermediate stage of deep learning, and the trends that are emerging in response to the challenges at this stage, including Interoperability and the multi-deployment options.
- Deep Learning on the Edge - Sep 19, 2018.
Detailed analysis into utilizing deep learning on the edge, covering both advantages and disadvantages and comparing this against more traditional cloud computing methods.
- Ready your Skills for a Cloud-First World with Google - Jul 20, 2018.
The Machine Learning with TensorFlow on Google Cloud Platform Specialization on Coursera will help you jumpstart your career, includes hands-on labs, and takes you from a strategic overview to practical skills in building real-world, accurate ML models.
- [eBook] Solving 4 Big Problems in Data Science - Mar 6, 2018.
Insights and tools from leading data science teams to accelerate results.
- Challenge Yourself to Think, Mar 19-22, Las Vegas - Feb 5, 2018.
Think 2018 is for those who seek inspiration and education, reinvention and innovation, want to connect with experts and seek progress. It is for understanding what is going on in the world around AI, Cloud, Data, Security, and Systems and discovering what’s possible. Use code TK18CAC to save.
- 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.
- 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.
- Benchmarking Big Data SQL Platforms in the Cloud - Sep 21, 2017.
TPC-DS benchmarks demonstrate Databricks Runtime 3.0's superior performance. Sign-up for a Databricks account to get fastest performance.
- Big Data Architecture: A Complete and Detailed Overview - Sep 19, 2017.
Data scientists may not be as educated or experienced in computer science, programming concepts, devops, site reliability engineering, non-functional requirements, software solution infrastructure, or general software architecture as compared to well-trained or experienced software architects and engineers.
- 3 Levers for Getting the Most Out of Amazon Redshift and AWS, Aug 29 - Aug 22, 2017.
Learn how to optimize your Amazon Redshift instance, critical metrics for smart investments in cloud infrastructure, and best practices to scale your AWS investment.
- Digital Transformation through Data Democratization - Jul 31, 2017.
Digital innovators will succeed because enterprise data doesn’t belong to silos and data has immense value, but only if available as a “whole”, to allow full picture of the enterprise rather than short term trends or baseline BI reports.
- Usage Patterns and the Economics of the Public Cloud - Jul 6, 2017.
Research in economics and operations management posits that dynamic pricing is critically important when capacity is fixed (at least in the short run) and fixed costs represent a substantial fraction of total costs.
- The Internet of Things in the Cloud - May 11, 2017.
Cloud computing is the next evolutionary step in Internet-based computing, which provides the means for delivering ICT resources as a service. Internet-of-Things can benefit from the scalability, performance and pay-as-you-go nature of cloud computing infrastructures.
- The dynamics between AI and IoT - Apr 18, 2017.
We see the need for a new type of Engineer who will combine knowledge from Electronics & IoT with Machine learning, AI, Robotics, Cloud and Data management (devops).
- “Data For Climate Action” Challenge – call for research proposals - Mar 13, 2017.
The challenge is to harness data science and big data from the private sector to fight climate change. Data scientists, researchers, and innovators - submit proposals at DataForClimateAction.org by 10 April 2017.
- The HPI Future SOC Lab offers researchers free access to a powerful Big Data infrastructure - Mar 10, 2017.
The HPI Future SOC (Service-Oriented Computing) Lab is a cooperation of the Hasso Plattner Institute (HPI) and industrial partners, providing free access to a powerful Big Data & Computing infrastructure. It is now accepting project proposals for 2017.
- 89degrees: SAS Administrator - Feb 16, 2017.
Seeking a SAS Administrator who will be responsible for the architecture, implementation and support of our enterprise-scale SAS environments hosted within 89 Degrees’ data center or in the Cloud.
- Inside Industry 4.0: What’s Driving The Fourth Industrial Revolution? - Oct 24, 2016.
In the history of mankind and past three major industrial revolutions, horizontal innovations like wheel, steam engine, electricity and integrated chips have always been the crux of it and they changed the world dramatically. Well, fourth one is on its way! Want to know what’s driving it? Have a read at this crisp article.
- The Inside Scoop on Apache Sqoop, Aug 25 Webinar - Aug 23, 2016.
Last chance! Register for Aug 25 webinar to learn about the best practices for using Apache Sqoop and interoperability with JDBC data sources from relational to cloud.
- Big Data Key Terms, Explained - Aug 11, 2016.
Just getting started with Big Data, or looking to iron out the wrinkles in your current understanding? Check out these 20 Big Data-related terms and their concise definitions.
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- The Inside Scoop on Apache Sqoop - Aug 8, 2016.
Check out this webinar to learn about the best practices for using Sqoop and interoperability with JDBC data sources from relational to cloud. Register today!
- 5 Big Data Projects You Can No Longer Overlook - Jul 21, 2016.
Check out 5 Big Data projects that you are not likely to have seen before, but which may be useful to you, and perhaps even scratch an itch you didn't know you had.
- Cloud Computing Key Terms, Explained - Jun 9, 2016.
A concise overview of 20 core cloud computing ecosystem concepts. The focus here is on the terminology, not The Big Picture.
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- HPI Future SOC Lab offers researchers free access to a powerful Big Data & Computing infrastructure - Feb 19, 2016.
The HPI Future SOC (Service-Oriented Computing) Lab is a cooperation of the Hasso Plattner Institute (HPI) and industrial partners, providing free access to a powerful Big Data & Computing infrastructure. It is now accepting project proposals.
- Data Analytics Boosting Digital Engagement at Australian Open 2016 - Jan 25, 2016.
Advanced analytics and visualization is enhancing fan experience and operational excellence at Australian Open 2016
- Microsoft: Data Solution Architect - Dec 2, 2015.
Drive high priority customer initiatives, leveraging Azure data services to solve the biggest and most complex data challenges faced by Microsoft enterprise customers.
- Computing Platforms for Analytics, Data Mining, Data Science - Apr 1, 2015.
The poll results suggest a split between a majority of data miners and data scientists who work with growing but still "PC-size", small GB-sized data, and a smaller group of Big Data analysts who work with cloud-sized data. Cloud computing, Unix, and especially Mac gained in popularity.
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- Interview: Dave McCrory, Basho on Distributed Database Needs of a Future Enterprise - Mar 16, 2015.
We discuss the future of distributed storage for enterprise, Scale-up vs. Scale-out, software design patterns in Cloud era, microservices model and the place for legacy database in modern enterprise IT.
- New Poll: Computing platform for your analytics, data mining, data science work or research - Mar 14, 2015.
New KDnuggets Poll is asking: What computing platform you use for analytics, data mining, data science work or research? Please vote.
- Simplilearn Big Data and Analytics Courses – CAREER30 - Mar 12, 2015.
Get Big Data and Analytics certification - a big plus for your career - with Simplilearn courses on Analytics, Big Data, Hadoop, SAS, R, Cloud Computing, and more, now at 30% discounted prices until Mar 30.
- Top stories for Dec 21-27: 2015 Predictions for big data and data science; The Big Data of Wearables - Dec 28, 2014.
2015 Predictions: What will happen to big data and data science?; The Big Data of Wearables; Open Source Tools for Machine Learning; FICO CAO sees a Post-Big Data World.
- Interview: Mac Devine, CTO, IBM Cloud on the Conflux of Cloud, IoT & Big Data - Dec 26, 2014.
We discuss the implications of Cloud Speed of technological advancement, significant trends in Internet of Things (IoT), future of cloud computing and more.
- Interview: Mac Devine, CTO, IBM Cloud on the Fast Approaching Perfect Storm - Dec 24, 2014.
We discuss why we should anticipate a technology perfect storm soon, Enterprise IT challenges, distinct capabilities of IBM BlueMix and more.
- Simplilearn Big Data and Analytics courses, 30% off - Dec 8, 2014.
Keep pace with the competition - upgrade your Big Data and Analytics skills with Simplilearn online courses in Cloud computing, Hadoop, SAS, R and more, now 30% off until Dec 31, 2014.
- EURECOM: Faculty Position in Data Mining and Machine Learning - Nov 20, 2014.
EURECOM, graduate school and a research center in communication systems, seeks qualified applicants interested in Big Data and Cloud computing for a tenured assistant professor position.
- Why Azure ML is the Next Big Thing for Machine Learning? - Nov 17, 2014.
With advanced capabilities, free access, strong support for R, cloud hosting benefits, drag-and-drop development and many more features, Azure ML is ready to take the consumerization of ML to the next level.
- iMathCloud, Python Data Science Platform - Nov 10, 2014.
iMathResearch presents its first tool for big data analysis, offering easy access to computational tools, a simple Python-based interface, cloud-based collaboration, and private computational instances.
- Interview: Arpit Gupta, CEO, Actionable Analytics on Enterprise Challenges in Big Data and Cloud - Aug 24, 2014.
We discuss Actionable Analytics start-up, enterprise challenges in Big Data, relationship with cloud computing, metrics vs. insights, Big Data expectations and more.
- KDnuggets Interview: Michael Brodie on Data Curation, Cloud Computing, Startup Quality, Verizon (part 2) - Apr 28, 2014.
The second part of our exclusive interview focuses on Data Curation, Cloud Computing, Data Tamer and Jisto startups, and his experience as a chief Scientist of Verizon - and how that relates to teenager never tidying a room for 60 years.