Search results for How to Get Funded

Found 66 documents, 5920 searched:

• Whose Responsibility Is It To Get Generative AI Right?

  The limitless possibilities of the technology that transcends boundaries.

  https://www.kdnuggets.com/2023/08/whose-responsibility-get-generative-ai-right.html

• I wasn’t getting hired as a Data Scientist. So I sought data on who is.">I wasn’t getting hired as a Data Scientist. So I sought data on who is.

  Instead of focusing on skills thought to be required of data scientists, we can look at what they have actually done before.

  https://www.kdnuggets.com/2019/09/getting-hired-data-scientist-sought-data.html

• New-Age Machine Learning Algorithms in Retail Lending">New-Age Machine Learning Algorithms in Retail Lending

  We review the application of new age Machine Learning algorithms for better Customer Analytics in Lending and Credit Risk Assessment.

  https://www.kdnuggets.com/2017/09/machine-learning-algorithms-lending.html

• Deep Learning – Past, Present, and Future">Deep Learning – Past, Present, and Future

  There is a lot of buzz around deep learning technology. First developed in the 1940s, deep learning was meant to simulate neural networks found in brains, but in the last decade 3 key developments have unleashed its potential.

  https://www.kdnuggets.com/2017/05/deep-learning-big-deal.html

• KDnuggets™ News 14:n27, Oct 22

  Features | Software | Opinions | Interviews | Reports | News | Webcasts | Courses | Meetings | Jobs | Academic | Publications | Tweets Read more »

  https://www.kdnuggets.com/2014/n27.html

• KDnuggets™ News 14:n24, Sep 18

  Features | Software | News | Opinions | Interviews | Reports | Webcasts | Courses | Meetings | Jobs | Academic | Publications | Tweets Read more »

  https://www.kdnuggets.com/2014/n24.html

• KDnuggets™ News 14:n16, Jun 25

  Features (5) | Software (1) | Opinions (2) | News (2) | Webcasts (1) | Courses (1) | Meetings and Reports (6) | Jobs (7) Read more »

  https://www.kdnuggets.com/2014/n16.html

• KDnuggets™ News 13:n27, Nov 13

  Features (10) | Software (4) | Webcasts (3) | Courses, Events (5) | Meetings (3) | Jobs (7) | Academic (4) | Competitions (2) | Publications Read more »

  https://www.kdnuggets.com/2013/n27.html

• KDnuggets™ News 13:n23, Sep 24

  Features (8) | Software (3) | Webcasts (2) | Courses, Events (4) | Meetings (3) | Jobs (10) | Academic (3) | Competitions (1) | Publications Read more »

  https://www.kdnuggets.com/2013/n23.html

• KDnuggets™ News 13:n21, Aug 28

  Features (9) | Software (1) | Webcasts (2) | Courses, Events (3) | Meetings (4) | Jobs (5) | Academic (3) | Competitions (1) | Publications Read more »

  https://www.kdnuggets.com/2013/n21.html

• KDnuggets™ News 13:n05, Feb 27

  Features (6) | Software (1) | Webcasts (3) | Courses, Events (2) | Jobs (5) | Academic (1) | Competitions (2) | Publications (3) | Tweets Read more »

  https://www.kdnuggets.com/2013/n05.html

• KDnuggets™ News 13:n02, Jan 30

  Features (10) | Software (4) | Courses, Events (2) | Webcasts (3) | Jobs (12) | Academic (5) | Competitions (4) | Publications (12) | NewsBriefs Read more »

  https://www.kdnuggets.com/2013/n02.html

• Expert Insights on Developing Safe, Secure, and Trustworthy AI Frameworks

  In alignment with President Biden's recent Executive Order emphasizing safe, secure, and trustworthy AI, we share our Trusted AI (TAI) lessons learned two years into the course of our US Federally funded TAI research projects.

  https://www.kdnuggets.com/expert-insights-on-developing-safe-secure-and-trustworthy-ai-frameworks

• Generative AI: The First Draft, Not Final

  This article gives a high-level overview of how LLMs work and their attendant limitations with accessible explanations and anecdotes throughout the piece. We also present advice on how people can introduce them into their workflows.

  https://www.kdnuggets.com/generative-ai-the-first-draft-not-final

• AI and Open Source Software: Separated at Birth?

  In this article, Luis shares with readers his thoughts on the intersection of open source software and machine learning and what the future might bring. Many articles cover how open source software is used by the machine learning community but this post focuses on the similarities between the two areas of practice and what machine learning can and can’t learn from open source software.

  https://www.kdnuggets.com/ai-and-open-source-software-separated-at-birth

• Who Will Make Money from the Generative AI Gold Rush?

  Buckle up for the Generative AI gold rush! Will BigTech rule with its picks and shovels? Which startups will strike it rich? Will “copilot for X” be the business strategy to hit pay dirt? How can startups dig moats to keep out other prospectors? And will the US once again have the richest gold seams?

  https://www.kdnuggets.com/2023/08/make-money-generative-ai-gold-rush.html

• Baize: An Open-Source Chat Model (But Different?)

  So what's new in the LLM space? Meet Baize, an open-source chat model that leverages the conversational capabilities of ChatGPT. Learn how Baize works, its advantages, limitations, and more.

  https://www.kdnuggets.com/2023/04/baize-opensource-chat-model-different.html

• 9 Top Platforms to Practice Key Data Science Skills

  Which platforms would I recommend as a go-to for learning and practicing data science skills? The list would change every day, depending on my mood. Here’s today’s list with an overview of each platform.

  https://www.kdnuggets.com/2023/03/9-top-platforms-practice-key-data-science-skills.html

• We Don’t Need Data Scientists, We Need Data Engineers

  As more people are entering the field of Data Science and more companies are hiring for data-centric roles, what type of jobs are currently in highest demand? There is so much data in the world, and it just keeps flooding in, it now looks like companies are targeting those who can engineer that data more than those who can only model the data.

  https://www.kdnuggets.com/2021/02/dont-need-data-scientists-need-data-engineers.html

• Machine Learning Textbook: Stochastic Processes and Simulations

  The 100 page book on stochastic processes. Published in 2022. This off-the-beaten-path machine learning tutorial is designed for busy professionals, researchers and students eager to learn and apply methods ranging from simple to advanced, in a minimum amount of time. Offered with data sets, source code, videos, spreadsheets and solved exercises.

  https://www.kdnuggets.com/2022/03/datashaping-machine-learning-textbook-stochastic-processes-simulations.html

• Demystifying Bad Science

  Rigorous science is challenging and any study can be questioned. Deception is part of human nature and scientists are human, as are journalists and policymakers. We are too and must be careful not to trust a study just because we find it exciting, or because it comforts us or conforms to our beliefs.

  https://www.kdnuggets.com/2022/01/demystifying-bad-science.html

• Surpassing Trillion Parameters and GPT-3 with Switch Transformers – a path to AGI?">Surpassing Trillion Parameters and GPT-3 with Switch Transformers – a path to AGI?

  Ever larger models churning on increasingly faster machines suggest a potential path toward smarter AI, such as with the massive GPT-3 language model. However, new, more lean, approaches are being conceived and explored that may rival these super-models, which could lead to a future with more efficient implementations of advanced AI-driven systems.

  https://www.kdnuggets.com/2021/10/trillion-parameters-gpt-3-switch-transformers-path-agi.html

• Awesome list of datasets in 100+ categories

  With an estimated 44 zettabytes of data in existence in our digital world today and approximately 2.5 quintillion bytes of new data generated daily, there is a lot of data out there you could tap into for your data science projects. It's pretty hard to curate through such a massive universe of data, but this collection is a great start. Here, you can find data from cancer genomes to UFO reports, as well as years of air quality data to 200,000 jokes. Dive into this ocean of data to explore as you learn how to apply data science techniques or leverage your expertise to discover something new.

  https://www.kdnuggets.com/2021/05/awesome-list-datasets.html

• DeepMind’s AlphaFold & the Protein Folding Problem

  Recently, DeepMind's AlphaFold made impressive headway in the protein structure prediction problem. Read this for an overview and explanation.

  https://www.kdnuggets.com/2021/03/deepmind-alphafold-protein-folding-problem.html

• Moving from Data Science to Machine Learning Engineering

  The world of machine learning — and software — is changing. Read this article to find out how, and what you can do to stay ahead of it.

  https://www.kdnuggets.com/2020/11/moving-data-science-machine-learning-engineering.html

• AI in Healthcare: A review of innovative startups

  The AI innovation in healthcare has been overwhelming with the Global Healthcare AI Market accounting for $0.95 billion in 2017, and is expected to reach $19.25 billion by 2026. What drives this vibrant growth?

  https://www.kdnuggets.com/2020/09/ai-healthcare-review-innovative-startups.html

• Hand labeling is the past. The future is #NoLabel AI

  Data labeling is so hot right now… but could this rapidly emerging market face disruption from a small team at Stanford and the Snorkel open source project, which enables highly efficient programmatic labeling that is 10 to 1,000x as efficient as hand labeling?

  https://www.kdnuggets.com/2020/02/hand-labeling-past-future-nolabel-ai.html

• Four questions to help accurately scope analytics engineering project

  Being really good at scoping analytics projects is crucial for team productivity and profitability. You can consistently deliver on time if you work out the issue first, and these four questions can help you prepare.

  https://www.kdnuggets.com/2019/10/four-questions-scope-analytics-engineering-project.html

• A European Approach to Master’s Degrees in Data Science">A European Approach to Master’s Degrees in Data Science

  Data science education in Europe has been reevaluated and new recommendations are leading the way to the next generation of data science Master's courses to better support and train students.

  https://www.kdnuggets.com/2019/10/european-approach-masters-data-science.html

• Jobs in Data Science, Machine Learning, AI & Analytics

  To add a free short entry here for a job related to Data Science, Machine Learning, AI or Analytics, email the following 5 items to Read more »

  https://www.kdnuggets.com/jobs/index.html

• An Overview of Python’s Datatable package

  Modern machine learning applications need to process a humongous amount of data and generate multiple features. Python’s datatable module was created to address this issue. It is a toolkit for performing big data (up to 100GB) operations on a single-node machine, at the maximum possible speed.

  https://www.kdnuggets.com/2019/08/overview-python-datatable-package.html

• AI: Arms Race 2.0

  An analysis of the current state of the competition between US, Europe, and China in AI, examining research, patent publications, global datasphere, devices and IoT, people, and more.

  https://www.kdnuggets.com/2019/03/ai-arms-race-20.html

• Text Preprocessing in Python: Steps, Tools, and Examples

  We outline the basic steps of text preprocessing, which are needed for transferring text from human language to machine-readable format for further processing. We will also discuss text preprocessing tools.

  https://www.kdnuggets.com/2018/11/text-preprocessing-python.html

• Financial Data Analysis – Data Processing 1: Loan Eligibility Prediction

  In this first part I show how to clean and remove unnecessary features. Data processing is very time-consuming, but better data would produce a better model.

  https://www.kdnuggets.com/2018/09/financial-data-analysis-loan-eligibility-prediction.html

• Programming Best Practices For Data Science">Programming Best Practices For Data Science

  In this post, I'll go over the two mindsets most people switch between when doing programming work specifically for data science: the prototype mindset and the production mindset.

  https://www.kdnuggets.com/2018/08/programming-best-practices-data-science.html

• The Current Hype Cycle in Artificial Intelligence

  Over the past decade, the field of artificial intelligence (AI) has seen striking developments. As surveyed in, there now exist over twenty domains in which AI programs are performing at least as well as (if not better than) humans.

  https://www.kdnuggets.com/2018/02/current-hype-cycle-artificial-intelligence.html

• Natural Language Processing Library for Apache Spark – free to use

  Introducing the Natural Language Processing Library for Apache Spark - and yes, you can actually use it for free! This post will give you a great overview of John Snow Labs NLP Library for Apache Spark.

  https://www.kdnuggets.com/2017/11/natural-language-processing-library-apache-spark.html

• 7 Types of Artificial Neural Networks for Natural Language Processing">7 Types of Artificial Neural Networks for Natural Language Processing

  What is an artificial neural network? How does it work? What types of artificial neural networks exist? How are different types of artificial neural networks used in natural language processing? We will discuss all these questions in the following article.

  https://www.kdnuggets.com/2017/10/7-types-artificial-neural-networks-natural-language-processing.html

• Beautiful Python Visualizations: An Interview with Bryan Van de Ven, Bokeh Core Developer

  Read this insightful interview with Bokeh's core developer, Bryan Van de Ven, and gain an understanding of what Bokeh is, when and why you should use it, and what makes Bryan a great fit for helming this project.

  https://www.kdnuggets.com/2017/08/interview-bryan-van-de-ven-bokeh.html

• The Most Underutilized Function in SQL

  Find out why md5() is an SQL function that's used surprisingly often, and find out how -- and why -- you can use it yourself.

  https://www.kdnuggets.com/2017/03/most-underutilized-function-sql.html

• Academic, Research Positions in Big Data, Data Mining, Data Science, Machine Learning

    To add here a short entry for an academic or research position related to AI, Big Data, Data Science, or Machine Learning, email 5 Read more »

  https://www.kdnuggets.com/academic/index.html

• Automated Machine Learning: An Interview with Randy Olson, TPOT Lead Developer

  Read an insightful interview with Randy Olson, Senior Data Scientist at University of Pennsylvania Institute for Biomedical Informatics, and lead developer of TPOT, an open source Python tool that intelligently automates the entire machine learning process.

  https://www.kdnuggets.com/2016/11/autoamted-machine-learning-interview-randy-olson-tpot.html

• EDISON Data Science Framework to define the Data Science Profession

  EDISON Data Science Framework provides conceptual, instructional and policy components required to establish the Data Science profession.

  https://www.kdnuggets.com/2016/10/edison-data-science-framework.html

• Introducing Dask for Parallel Programming: An Interview with Project Lead Developer

  Introducing Dask, a flexible parallel computing library for analytics. Learn more about this project built with interactive data science in mind in an interview with its lead developer.

  https://www.kdnuggets.com/2016/09/introducing-dask-parallel-programming.html

• Data Mining Tip: How to Use High-cardinality Attributes in a Predictive Model

  High-cardinality nominal attributes can pose an issue for inclusion in predictive models. There exist a few ways to accomplish this, however, which are put forward here.

  https://www.kdnuggets.com/2016/08/include-high-cardinality-attributes-predictive-model.html

• The Hard Problems AI Can’t (Yet) Touch

  It's tempting to consider the progress of AI as though it were a single monolithic entity, advancing towards human intelligence on all fronts. But today's machine learning only addresses problems with simple, easily quantified objectives

  https://www.kdnuggets.com/2016/07/hard-problems-ai-cant-yet-touch.html

• Are Deep Neural Networks Creative?

  Deep neural networks routinely generate images and synthesize text. But does this amount to creativity? Can we reasonably claim that deep learning produces art?

  https://www.kdnuggets.com/2016/05/deep-neural-networks-creative-deep-learning-art.html

• The ICLR Experiment: Deep Learning Pioneers Take on Scientific Publishing

  Deep learning pioneers Yann LeCun and Yoshua Bengio have undertaken a grand experiment in academic publishing. Embracing a radical level of transparency and unprecedented public participation, they've created an opportunity not only to find and vet the best papers, but also to gather data about the publication process itself.

  https://www.kdnuggets.com/2016/02/iclr-deep-learning-scientific-publishing-experiment.html

• Deep Learning Transcends the Bag of Words

  Generative RNNs are now widely popular, many modeling text at the character level and typically using unsupervised approach. Here we show how to generate contextually relevant sentences and explain recent work that does it successfully.

  https://www.kdnuggets.com/2015/12/deep-learning-outgrows-bag-words-recurrent-neural-networks.html

• MetaMind Mastermind Richard Socher: Uncut Interview

  In a wide-ranging interview, Richard Socher opens up about MetaMind, deep learning, the nature of corporate research, and the future of machine learning.

  https://www.kdnuggets.com/2015/10/metamind-mastermind-richard-socher-deep-learning-interview.html

• Does Deep Learning Come from the Devil?

  Deep learning has revolutionized computer vision and natural language processing. Yet the mathematics explaining its success remains elusive. At the Yandex conference on machine learning prospects and applications, Vladimir Vapnik offered a critical perspective.

  https://www.kdnuggets.com/2015/10/deep-learning-vapnik-einstein-devil-yandex-conference.html

• Recycling Deep Learning Models with Transfer Learning

  Deep learning exploits gigantic datasets to produce powerful models. But what can we do when our datasets are comparatively small? Transfer learning by fine-tuning deep nets offers a way to leverage existing datasets to perform well on new tasks.

  https://www.kdnuggets.com/2015/08/recycling-deep-learning-representations-transfer-ml.html

• Deep Learning and the Triumph of Empiricism

  Theoretical guarantees are clearly desirable. And yet many of today's best-performing supervised learning algorithms offer none. What explains the gap between theoretical soundness and empirical success?

  https://www.kdnuggets.com/2015/07/deep-learning-triumph-empiricism-over-theoretical-mathematical-guarantees.html

• The Myth of Model Interpretability

  Deep networks are widely regarded as black boxes. But are they truly uninterpretable in any way that logistic regression is not?

  https://www.kdnuggets.com/2015/04/model-interpretability-neural-networks-deep-learning.html

• Do We Need More Training Data or More Complex Models?

  Do we need more training data? Which models will suffer from performance saturation as data grows large? Do we need larger models or more complicated models, and what is the difference?

  https://www.kdnuggets.com/2015/03/more-training-data-or-complex-models.html

• Data Science’s Most Used, Confused, and Abused Jargon

  As data science has spread through the mainstream, so too has a dense vocabulary of ill-defined jargon. In a split-personality post, we offer several perspectives on many of data science's most confused terms.

  https://www.kdnuggets.com/2015/02/data-science-confusing-jargon-abused.html

• (Deep Learning’s Deep Flaws)’s Deep Flaws

  Recent press has challenged the hype surrounding deep learning, trumpeting several findings which expose shortcomings of current algorithms. However, many of deep learning's reported flaws are universal, affecting nearly all machine learning algorithms.

  https://www.kdnuggets.com/2015/01/deep-learning-flaws-universal-machine-learning.html

• The High Cost of Maintaining Machine Learning Systems

  Google researchers warn of the massive ongoing costs for maintaining machine learning systems. We examine how to minimize the technical debt.

  https://www.kdnuggets.com/2015/01/high-cost-machine-learning-technical-debt.html

• MetaMind Competes with IBM Watson Analytics and Microsoft Azure Machine Learning

  While Microsoft and IBM rush to bring data science and visualization to the masses, MetaMind follows another path, offering deep learning as a service.

  https://www.kdnuggets.com/2015/01/metamind-ibm-watson-analytics-microsoft-azure-machine-learning.html

• Differential Privacy: How to make Privacy and Data Mining Compatible

  Can privacy coexist with machine learning and data mining? Differential privacy allows the learning of general characteristics of populations while guaranteeing the privacy of individual records.

  https://www.kdnuggets.com/2015/01/differential-privacy-data-mining-compatible.html

• IBM Watson Analytics vs. Microsoft Azure Machine Learning (Part 1)

  IBM Watson Analytics prototype seeks to abstract away data science, taking ordinary natural language queries and answering them based on the content of uploaded datasets. Microsoft Azure Machine Learning goes the opposite route, streamlining existing data mining methodology for fast results and integration with MS's other cloud services.

  https://www.kdnuggets.com/2014/12/ibm-watson-analytics-microsoft-azure-machine-learning-p1.html

• Geoff Hinton AMA: Neural Networks, the Brain, and Machine Learning

  In a wide-ranging Q&A, Geoff Hinton addresses the future of deep learning, its biological inspirations, and his research philosophy.

  https://www.kdnuggets.com/2014/12/geoff-hinton-ama-neural-networks-brain-machine-learning.html

• Do you need a Masters Degree to become a Data Scientist?

  Leading analytics experts answer the question: "Do you need a Masters Degree to become a Data Scientist?" Read practical tips and interesting commentary.

  https://www.kdnuggets.com/2014/06/masters-degree-become-data-scientist.html

• Is Data Scientist the right career path for you? Candid advice

  Candid advice from an industry veteran reveals the true picture behind the much-talked-about Data Scientist "glamour" and helps people have the right expectations for a Data Science career.

  https://www.kdnuggets.com/2014/03/data-scientist-right-career-path-candid-advice.html

• 2013 Nov: Analytics, Big Data, Data Mining and Data Science Posts

  All (116) | News, Software (28) | Courses, Events (23) | Jobs | Academic | Publications (36) Yahoo SAMOA, Open Source Platform for Mining Big Read more »

  https://www.kdnuggets.com/2013/11/index.html

• Data Mining / Analytic News, Aug 2013

  News, Software (33) | Courses, Events (28) | Jobs | Academic | Publications (31) Top Languages for analytics, data mining, data science - Aug 27, Read more »

  https://www.kdnuggets.com/2013/08/index.html