- Cloud ML In Perspective: Surprises of 2021, Projections for 2022 - Dec 16, 2021.
Let’s take a closer look on Cloud ML market in 2021 in retrospective (with occasional drills into realities of 2020, too). Read this in-depth analysis.
2022 Predictions, Cloud, Machine Learning
- Data Science & Analytics Industry Main Developments in 2021 and Key Trends for 2022 - Dec 14, 2021.
We have solicited insights from experts at industry-leading companies, asking: "What were the main AI, Data Science, Machine Learning Developments in 2021 and what key trends do you expect in 2022?" Read their opinions here.
2022 Predictions, AI, Analytics, Cloud, Data Lake, Data Science, Data Warehouse, Deep Learning, Machine Learning, Synthetic Data
- SAS Analytics Pro – now available for on-site or containerized cloud-native deployment – providing your entry point into SAS Viya - Nov 9, 2021.
Now, SAS Analytics Pro includes a new option for containerized cloud-native deployment. This makes SAS Analytics Pro a perfect entry point into SAS Viya.
Cloud, Containers, SAS
- If You Can Write Functions, You Can Use Dask - Sep 21, 2021.
This article is the second article of an ongoing series on using Dask in practice. Each article in this series will be simple enough for beginners, but provide useful tips for real work. The first article in the series is about using LocalCluster.
Cloud, Dask, Python, Saturn Cloud
- Stack Overflow Survey Data Science Highlights - Aug 20, 2021.
The results of the 2021 Stack Overflow Developer Survey were recently released, which is a fascinating snapshot of today's developers and the tools they are using. Have a look at some selections from the report, particularly those which may be of interest to data professionals.
Cloud, Data Science, Databases, Developers, Programming, Programming Languages, StackOverflow, Survey
Prefect: How to Write and Schedule Your First ETL Pipeline with Python - Aug 16, 2021.
Workflow management systems made easy — both locally and in the cloud.
Cloud, ETL, Pipeline, Python
- Bootstrap a Modern Data Stack in 5 minutes with Terraform - Aug 6, 2021.
What is a Modern Data Stack and how do you deploy one? This guide will motivate you to start on this journey with setup instructions for Airbyte, BigQuery, dbt, Metabase, and everything else you need using Terraform.
BigQuery, Cloud, Data Warehousing, dbt, Modern Data Stack
- In-Warehouse Machine Learning and the Modern Data Science Stack - Jun 24, 2021.
As your organization matures its data science portfolio and capabilities, establishing a modern data stack is vital to enabling such growth. Here, we overview various in-data warehouse machine learning services, and discuss each of their benefits and requirements.
Amazon Redshift, Analytics, BigQuery, Cloud, Data Science, Data Warehouse, Machine Learning, Modern Data Stack
- Create and Deploy Dashboards using Voila and Saturn Cloud - Jun 23, 2021.
Working with and training large datasets, maintaining them all in one place, and deploying them to production is a challenging job. In this article, we covered what Saturn Cloud is and how it can speed up your end-to-end pipeline, how to create dashboards using Voila and Python and publish them to production in just a few easy steps.
Analytics, Cloud, Dashboard, Data Science, Machine Learning, Python
- Super Charge Python with Pandas on GPUs Using Saturn Cloud - May 12, 2021.
Saturn Cloud is a tool that allows you to have 10 hours of free GPU computing and 3 hours of Dask Cluster computing a month for free. In this tutorial, you will learn how to use these free resources to process data using Pandas on a GPU. The experiments show that Pandas is over 1,000,000% slower on a CPU as compared to running Pandas on a Dask cluster of GPUs.
Cloud, GPU, Pandas, Python
- ETL in the Cloud: Transforming Big Data Analytics with Data Warehouse Automation - Apr 15, 2021.
Today, organizations are increasingly implementing cloud ETL tools to handle large data sets. With data sets becoming larger by the day, unified ETL tools have become crucial for data integration needs of enterprises.
Automation, Big Data, Big Data Analytics, Cloud, Data Analytics, Data Warehouse, ETL
- MongoDB in the Cloud: Three Solutions for 2021 - Mar 26, 2021.
An overview of pricing and compatibility for MongoDB Atlas, AWS DocumentDB, Azure Cosmos DB.
Cloud, Database, MongoDB, NoSQL
- Cloud Data Warehouse is The Future of Data Storage - Jan 12, 2021.
Today, cloud data storage accounts for 45% of all enterprise data and by Q2 2021, that number could grow to 53%. Now is the time to embrace cloud than now.
Cloud, Data Warehouse, Data Warehousing
- The Future of Cloud is Now - Dec 22, 2020.
Our recent survey of over 130 top data engineers, data architects, and executives uncovered details and trends of the current state of data engineering and DataOps.Read our survey report to learn more about these trends as well as our predictions for future obstacles and our recommendations for avoiding them.
Cloud, Data Engineering, Data Platform, Immuta, Survey
- Data Science in the Cloud with Dask - Oct 20, 2020.
Scaling large data analyses for data science and machine learning is growing in importance. Dask and Coiled are making it easy and fast for folks to do just that. Read on to find out how.
Cloud, Dask, Data Science, Python
- Machine Learning Model Deployment - Sep 30, 2020.
Read this article on machine learning model deployment using serverless deployment. Serverless compute abstracts away provisioning, managing severs and configuring software, simplifying model deployment.
Cloud, Deployment, Machine Learning, Modeling, Workflow
- Deploy a Machine Learning Pipeline to the Cloud Using a Docker Container - Jun 12, 2020.
In this tutorial, we will use a previously-built machine learning pipeline and Flask app to demonstrate how to deploy a machine learning pipeline as a web app using the Microsoft Azure Web App Service.
Cloud, Docker, Machine Learning, Pipeline, PyCaret, Python
10 Must-read Machine Learning Articles (March 2020) - Apr 9, 2020.
This list will feature some of the recent work and discoveries happening in machine learning, as well as guides and resources for both beginner and intermediate data scientists.
AI, API, Cloud, Data Analytics, Datasets, fast.ai, Machine Learning, Neural Networks, Social Media
- Introduction to Kubeflow MPI Operator and Industry Adoption - Mar 27, 2020.
Kubeflow just announced its first major 1.0 release recently. This post introduces the MPI Operator, one of the core components of Kubeflow, currently in alpha, which makes it easy to run synchronized, allreduce-style distributed training on Kubernetes.
Cloud, Kubeflow, Kubernetes, Machine Learning
- Serverless Machine Learning with R on Cloud Run - Feb 4, 2020.
Expedite the deployment of your machine models using serverless cloud infrastructure. In this tutorial, we explore creating and deploying a model which scraps real time Twitter data and returns interactive visualization using R.
Cloud, Machine Learning, R, Twitter
- Easy, One-Click Jupyter Notebooks - Jul 24, 2019.
All of the setup for software, networking, security, and libraries is automatically taken care of by the Saturn Cloud system. Data Scientists can then focus on the actual Data Science and not the tedious infrastructure work that falls around it
Big Data, Cloud, Data Science, Data Scientist, DevOps, Jupyter, Python, Saturn Cloud
- KDnuggets™ News 19:n24, Jun 26: Understand Cloud Services; Pandas Tips & Tricks; Master Data Preparation w/ Python - Jun 26, 2019.
Happy summer! This week on KDnuggets: Understanding Cloud Data Services; How to select rows and columns in Pandas using [ ], .loc, iloc, .at and .iat; 7 Steps to Mastering Data Preparation for Machine Learning with Python; Examining the Transformer Architecture: The OpenAI GPT-2 Controversy; Data Literacy: Using the Socratic Method; and much more!
Cloud, Data Preparation, Machine Learning, NLP, OpenAI, Pandas, Python
Top 10 Technology Trends of 2019 - Feb 7, 2019.
This article outlines 10 top trending technologies for 2019, a list which covers diverse topics such as security, IoT, reinforcement learning, energy sustainability, smart cities, and much more.
2019 Predictions, Automation, Cloud, Energy, IoT, Reinforcement Learning, Security, Trends
- KDnuggets™ News 18:n44, Nov 21: What is the Best Python IDE for Data Science?; Anticipating the next move in data science - Nov 21, 2018.
Also: Mastering The New Generation of Gradient Boosting; Top 10 Python Data Science Libraries; Predictive Analytics in 2018: Salaries & Industry Shifts; Sorry I didn't get that! How to understand what your users want; Best Deals in Deep Learning Cloud Providers: From CPU to GPU to TPU
Cloud, Data Science, Gradient Boosting, Interpretability, Machine Learning, Predictive Analytics, Python
- Deploying scikit-learn Models at Scale - Aug 29, 2018.
Find out how to serve your scikit-learn model in an auto-scaling, serverless environment! Today, we’ll take a trained scikit-learn model and deploy it on Cloud ML Engine.
Cloud, Google, Google Cloud, Machine Learning, Python, scikit-learn
- How to Set Up a Free Data Science Environment on Google Cloud - Aug 15, 2018.
In this post, we'll walk through how to set up a data science environment on Google Cloud Platform (GCP). Because of the economy of scale that cloud hosting companies provide, individuals or teams can affordably access powerful computers.
Cloud, Data Science, Google, Google Cloud, Jupyter
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.
Pages: 1 2
AI, Amazon, Azure ML, Cloud, Google, Google Cloud, Machine Learning, Microsoft, MLaaS, Sagemaker
- Deep Learning Made Easy with Deep Cognition - Dec 21, 2017.
So normally we do Deep Learning programming, and learning new APIs, some harder than others, some are really easy an expressive like Keras, but how about a visual API to create and deploy Deep Learning solutions with the click of a button? This is the promise of Deep Cognition.
Pages: 1 2
Cloud, Deep Learning, Keras, Neural Networks, TensorFlow
- 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.
Analytics, Big Data, Big Data Architecture, Cloud, Cloud Computing, Scalability, Software, Software Engineering
- 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.
Cloud, Cloud Computing, Economics
- Machine Learning in Real Life: Tales from the Trenches to the Cloud – Part 1 - Jun 8, 2017.
We live in a world where everyone knows enough about the Buzzwords “Deep Learning” and “Big Data”... we also live in a world where if you’re a developer you can, while knowing nothing about machine learning, go from zero to training a OCR model in the space of an hour.
Cloud, Machine Learning, Production
- 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.
Cloud, Cloud Computing, Internet of Things, IoT, Scalability
- AI is not at all like Mobile/Cloud/SaaS - Feb 10, 2017.
AI is a hard problem and will take much longer to solve in any scope. The sudden uptick in interest may revert back to normal, but the cycle of work will be longer, much more diverse, and interesting than Mobile/Cloud/SaaS.
AI, Cloud, Hype, Mobile
- Why the Data Scientist and Data Engineer Need to Understand Virtualization in the Cloud - Jan 25, 2017.
This article covers the value of understanding the virtualization constructs for the data scientist and data engineer as they deploy their analysis onto all kinds of cloud platforms. Virtualization is a key enabling layer of software for these data workers to be aware of and to achieve optimal results from.
Pages: 1 2
Cloud, Data Engineer, Data Engineering, Data Science, Data Scientist, Virtualization
- HPE Haven OnDemand: Powerful Data Connectors for the Cloud and Enterprise - Sep 1, 2016.
HPE Haven OnDemand simplifies how you can interact with data, allowing it to be transformed into an asset anytime, anywhere. Find out how the Connector APIs can facilitate this interaction.
Pages: 1 2
API, Cloud, Haven OnDemand, HPE, Python
- Introducing Cloud Hosted Deep Learning Models - Jul 21, 2016.
Algorithmia introduces a solution for hosting and distributing locally-trained deep learning models on Algorithmia using GPUs in the cloud, where they become smart API endpoints for other developers to use.
Algorithmia, API, Cloud, Deep Learning, Diego Oppenheimer
- Machine Learning Trends and the Future of Artificial Intelligence - Jun 22, 2016.
The confluence of data flywheels, the algorithm economy, and cloud-hosted intelligence means every company can now be a data company, every company can now access algorithmic intelligence, and every app can now be an intelligent app.
Algorithmia, Algorithms, Artificial Intelligence, Cloud, Machine Intelligence, Machine Learning
- 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.
Pages: 1 2
AWS, Cloud, Cloud Computing, Explained, Key Terms, PaaS, SaaS
- Interview: Reiner Kappenberger, HP Security Voltage on How to Secure Data-in-Motion - Jul 9, 2015.
We discuss the security concerns in Big Data, challenges in securing Big Data locally and over cloud, and open source solutions – Knox and Ranger.
Challenges, Cloud, HP, HP Security Voltage, Interview, Open Source, Reiner Kappenberger, Security
- Hadoop as a Service: 18 Cloud Options - Apr 2, 2015.
Hadoop as a service in the cloud makes big data applications and projects easier to approach and these 18 platforms each provide their own unique solutions.
AWS, Big Data Services, Cloud, Cloudera, Hadoop, Hortonworks, Information Management, MapR, Microsoft Azure
- Interview: Peter Alvaro, UC Berkeley, on Managing Asynchrony and Partial Failure - Dec 18, 2014.
We discuss the challenges in simultaneously managing asynchrony and partial failure, the problem of composition, research motivation, trends and more.
Challenges, Cloud, Peter Alvaro, Programming Languages, Recommendations, Trends, UC Berkeley
- KDnuggets Exclusive: Marten Mickos, SVP, HP on the Role of Open Source in Cloud industry - Nov 15, 2014.
In an exclusive interview with KDnuggets, Marten talks about HP’s Open Source strategy, evolution of Open Source production model, learning from the success of Open Source in Web, trends and more.
Career, Cloud, Helion, HP, Interview, Marten Mickos, Open Source, OpenStack
- KDnuggets Exclusive: Marten Mickos, SVP, HP on Why the Future Belongs to “Hybrid Clouds” - Nov 13, 2014.
In an exclusive interview with KDnuggets, Marten talks about the future of Eucalyptus (recently acquired by HP), defines Hybrid Clouds and their importance, and gives some tips for vendor selection.
AWS, Cloud, Helion, HP, HPE, Interview, Marten Mickos, OpenStack, PaaS
- Microsoft: Data Scientists in Redmond, Boston and Mountain View - Sep 25, 2014.
Join the excitement of Machine Learning in the Cloud at Microsoft fast-paced data science team in the Azure ML group, building machine learning powered intelligent web services and end to end solutions.
Boston-MA, Cloud, Data Scientist, Microsoft, Microsoft Azure, Mountain View-CA, Redmond-WA
- Microsoft: Data Scientist - Apr 30, 2014.
Join a fast paced data science team in the Microsoft Cloud + Enterprise organization building machine learning powered intelligent web services.
Cloud, Microsoft, Redmond-WA
- Microsoft: Data Scientist - Feb 28, 2014.
Join a fast paced data science team in the Microsoft Cloud + Enterprise organization building machine learning powered intelligent web services.
Cloud, Machine Learning, Microsoft, Web services
- Akamai: Principal Data Scientist - Jan 21, 2014.
Akamai is growing fast and so is the volume of data we manage - if you love analyzing and extracting meaningful insight from big data, and see it applied, this opportunity is for you.
Akamai, Cambridge-MA, Cloud
