Search results for iaas

Found 36 documents, 13736 searched:

• Beginner’s Guide to Cloud Computing

  Learn how cloud computing works, different types of models, top cloud platforms, and applications.

  https://www.kdnuggets.com/2023/01/beginner-guide-cloud-computing.html

• The Complete Data Engineering Study Roadmap

  Everything you need to know to start your career in Data Engineering.

  https://www.kdnuggets.com/2022/11/complete-data-engineering-study-roadmap.html

• Disentangling AI, Machine Learning, and Deep Learning

  The field of Artificial Intelligence is extremely broad and captures a winding history through the evolution of various sub-fields that experienced many ups and downs over the years. Appreciating AI within its historical contexts will enhance your communication with the public, colleagues, and potential hiring managers, as well as guide your thinking as you progress in the application and study of state-of-the-art techniques.

  https://www.kdnuggets.com/2021/05/disentangling-ai-machine-learning-deep-learning.html

• Top YouTube Machine Learning Channels

  These are the top 15 YouTube channels for machine learning as determined by our stated criteria, along with some additional data on the channels to help you decide if they may have some content useful for you.

  https://www.kdnuggets.com/2021/03/top-youtube-machine-learning-channels.html

• 5 Best Practices for Putting Machine Learning Models Into Production

  Our focus for this piece is to establish the best practices that make an ML project successful.

  https://www.kdnuggets.com/2020/10/5-best-practices-machine-learning-models-production.html

• Everything a Data Scientist Should Know About Data Management">Everything a Data Scientist Should Know About Data Management

  For full-stack data science mastery, you must understand data management along with all the bells and whistles of machine learning. This high-level overview is a road map for the history and current state of the expansive options for data storage and infrastructure solutions.

  https://www.kdnuggets.com/2019/10/data-scientist-data-management.html

• How To Get Funding For AI Startups

  What are the biggest challenges AI startups have when pitching to investors? Learn how to grab their attention with these recommendations on how to start building your AI company.

  https://www.kdnuggets.com/2019/06/funding-ai-startups.html

• Understanding Cloud Data Services">Understanding Cloud Data Services

  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.

  https://www.kdnuggets.com/2019/06/understanding-cloud-data-services.html

• Industry Predictions: AI, Machine Learning, Analytics & Data Science Main Developments in 2018 and Key Trends for 2019">Industry Predictions: AI, Machine Learning, Analytics & Data Science Main Developments in 2018 and Key Trends for 2019

  This is a collection of data science, machine learning, analytics, and AI predictions for next year from a number of top industry organizations. See what the insiders feel is on the horizon for 2019!

  https://www.kdnuggets.com/2018/12/predictions-industry-2019.html

• Cummins: Data Engineering Apps and Solutions Architect [Columbus, IN]

  Cummins is seeking a Data Engineering Apps and Solutions Architect in Columbus, IN, to focus on the specific Architecture, tools and environment optimization for the Data Engineering team within the Advanced Analytics organization and applied to Cummins standards worldwide.

  https://www.kdnuggets.com/jobs/18/12-13-cummins-data-engineering-apps-solutions-architect.html

• Intuitive Ensemble Learning Guide with Gradient Boosting

  This tutorial discusses the importance of ensemble learning with gradient boosting as a study case.

  https://www.kdnuggets.com/2018/07/intuitive-ensemble-learning-guide-gradient-boosting.html

• Genetic Algorithm Implementation in Python">Genetic Algorithm Implementation in Python

  This tutorial will implement the genetic algorithm optimization technique in Python based on a simple example in which we are trying to maximize the output of an equation.

  https://www.kdnuggets.com/2018/07/genetic-algorithm-implementation-python.html

• Beginners Ask “How Many Hidden Layers/Neurons to Use in Artificial Neural Networks?”">Beginners Ask “How Many Hidden Layers/Neurons to Use in Artificial Neural Networks?”

  By the end of this article, you could at least get the idea of how these questions are answered and be able to test yourself based on simple examples.

  https://www.kdnuggets.com/2018/07/beginners-ask-how-many-hidden-layers-neurons-neural-networks.html

• Packaging and Distributing Your Python Project to PyPI for Installation Using pip

  This tutorial will explain the steps required to package your Python projects, distribute them in distribution formats using steptools, upload them into the Python Package Index (PyPI) repository using twine, and finally installation using Python installers such as pip and conda.

  https://www.kdnuggets.com/2018/06/packaging-distributing-python-project-pypi-pip.html

• Complete Guide to Build ConvNet HTTP-Based Application using TensorFlow and Flask RESTful Python API">Complete Guide to Build ConvNet HTTP-Based Application using TensorFlow and Flask RESTful Python API

  In this tutorial, a CNN is to be built, and trained and tested against the CIFAR10 dataset. To make the model remotely accessible, a Flask Web application is created using Python to receive an uploaded image and return its classification label using HTTP.

  https://www.kdnuggets.com/2018/05/complete-guide-convnet-tensorflow-flask-restful-python-api.html

• 8 Useful Advices for Aspiring Data Scientists">8 Useful Advices for Aspiring Data Scientists

  I recently read Sebastian Gutierrez’s “Data Scientists at Work”, in which he interviewed 16 data scientists. I want to share the best answers that these data scientists gave for the question: "What advice would you give to someone starting out in data science?"

  https://www.kdnuggets.com/2018/05/8-useful-advices-aspiring-data-scientists.html

• Building Convolutional Neural Network using NumPy from Scratch">Building Convolutional Neural Network using NumPy from Scratch

  In this article, CNN is created using only NumPy library. Just three layers are created which are convolution (conv for short), ReLU, and max pooling.

  https://www.kdnuggets.com/2018/04/building-convolutional-neural-network-numpy-scratch.html

• Data Exchange and Marketplace, a New Business Model in Making

  This article covers how an ever-increasing amount of data will trigger the evolution of a new ecosystem that will spur entrepreneurial activity, offering an opportunity to start a wide range of new businesses.

  https://www.kdnuggets.com/2018/04/data-exchange-marketplace-business-model.html

• Derivation of Convolutional Neural Network from Fully Connected Network Step-By-Step

  What are the advantages of ConvNets over FC networks in image analysis? How is ConvNet derived from FC networks? Where the term convolution in CNNs came from? These questions are to be answered in this article.

  https://www.kdnuggets.com/2018/04/derivation-convolutional-neural-network-fully-connected-step-by-step.html

• 12 Useful Things to Know About Machine Learning">12 Useful Things to Know About Machine Learning

  This is a summary of 12 key lessons that machine learning researchers and practitioners have learned include pitfalls to avoid, important issues to focus on and answers to common questions.

  https://www.kdnuggets.com/2018/04/12-useful-things-know-about-machine-learning.html

• Are New Technologies Killing Their Ancestors?

  Are automatic feature learning models (e.g. CNN) killing their previous manually engineered models? This is an important question that is to be answered in this article.

  https://www.kdnuggets.com/2018/04/new-technologies-killing-ancestors.html

• Introduction to Optimization with Genetic Algorithm">Introduction to Optimization with Genetic Algorithm

  This article gives a brief introduction about evolutionary algorithms (EAs) and describes genetic algorithm (GA) which is one of the simplest random-based EAs.

  https://www.kdnuggets.com/2018/03/introduction-optimization-with-genetic-algorithm.html

• Digital Transformation through Data Democratization

  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.

  https://www.kdnuggets.com/2017/07/digital-transformation-data-democratization.html

• The Internet of Things in the Cloud

  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.

  https://www.kdnuggets.com/2017/05/internet-of-things-iot-cloud.html

• Unsupervised Investments: A Comprehensive Guide to AI Investors

  This article presents a list of 80 funds investing in Artificial Intelligence and Machine Learning.

  https://www.kdnuggets.com/2017/03/unsupervised-investments-guide-ai-investors.html

• SAP.iO Start-Up Incubator: Senior Data Scientist

  Looking for a passionate data scientist to help the startup teams in our incubator run efficiently, effectively, and enjoyably; analyze diverse data sets to provide actionable insights for each team.

  https://www.kdnuggets.com/jobs/16/11-09-sap-senior-data-scientist.html

• Why Not So Hadoop?

  Are Big Data and Hadoop synonymous? Not really, but they are often conflated. Has Hadoop lived up to its hype? In this article, we will look at a brief history of Hadoop and see where it stands today.

  https://www.kdnuggets.com/2016/09/why-not-so-hadoop.html

• IBM: Data Engineers/Data Scientists

  IBM is seeking Data Engineers/Data Scientists to combine cognitive computing/Watson technology with traditional data science/engineering and apply it at scale to transform enterprise business processes including: Operations, Marketing, Communications, Finance/Accounting, Supply chain, and Human Resources.

  https://www.kdnuggets.com/jobs/16/06-09-ibm-data-engineers-data-scientists.html

• Cloud Computing Key Terms, Explained

  A concise overview of 20 core cloud computing ecosystem concepts. The focus here is on the terminology, not The Big Picture.

  https://www.kdnuggets.com/2016/06/cloud-computing-key-terms-explained.html

• HPE Haven OnDemand and Microsoft Azure Machine Learning: Power Tools for Developers and Data Scientists

  While both HPE and Microsoft machine learning platforms offer numerous possibilities for developers and data scientists, HPE Haven OnDemand is a diverse collection of APIs for interacting with data designed with flexibility in mind, allowing developers to quickly perform data tasks in the cloud.

  https://www.kdnuggets.com/2016/03/hpe-haven-ondemand-microsoft-azure-machine-learning.html

• Top KDnuggets tweets, Dec 14-20: DeepLearning in a Nutshell: History and Training; Top 10 #MachineLearning Algorithms, updated

  Top 10 #MachineLearning Algorithms, updated; Cartoon: Surprise #DataScience #Recommendations; DeepLearning in a Nutshell: History and Training; Update: Google #TensorFlow #DeepLearning Is Improving.

  https://www.kdnuggets.com/2015/12/top-tweets-dec14-20.html

• Top KDnuggets tweets, Nov 10-16: 5 Books Every #Data Professional Needs; TensorFlow Disappoints – Google Deep Learning falls shallow

  Deep Learning for #Visual Question Answering; 5 Books Every #Data Professional Needs; Deep, excellent overview: A Statistical View of #DeepLearning; TensorFlow Disappoints - Google #DeepLearning falls shallow.

  https://www.kdnuggets.com/2015/11/top-tweets-nov10-16.html

• Trifacta – Wrangling US Flight Data, part 2

  This post shows how to use Trifacta to clean the data and enrich it with airport geo-locations and airline names, including filling missing values, and doing a lookup from another dataset. We also learn which is the best airline at O’Hare airport.

  https://www.kdnuggets.com/2015/05/trifacta-wrangling-us-flight-data-part2.html

• Simplilearn Big Data and Analytics courses, 30% off

  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.

  https://www.kdnuggets.com/2014/12/simplilearn-big-data-analytics-courses-30pct-off.html

• Top 10 Big Data Companies by Revenue

  IBM, HP, Dell, and SAP lead the list of Big Data companies with the most revenue from big data hardware, software, and IT services.

  https://www.kdnuggets.com/2014/12/top-10-big-data-companies-revenue.html

• Big Data for Executives 2014: Day 2 Highlights

  Highlights from the presentations by Big Data experts from McKinsey Solutions, SAP, Techfetch, Weather Analytics on Day 2 of Big Data for Executives 2014.

  https://www.kdnuggets.com/2014/05/big-data-executives-highlights-day-2.html