Search results for Funding Your Business

Found 50 documents, 5930 searched:

• Crafting an Elevator Pitch for your Data Science Startup

  If you are launching a data science startup, these tips will give you a head start as you seek capital for seed funding or your next level of growth.

  https://www.kdnuggets.com/2019/08/elevator-pitch-data-science-startup.html

• How to Showcase the Impact of Your Data Science Work

  You're a Data Scientist -- or preparing to land your first job -- and communicating your work to others, especially employers, so they understand your impact is essential. These five tips will help you help others appreciate your data science.

  https://www.kdnuggets.com/2019/07/showcase-impact-data-science-work.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

• Building a GPU Machine vs. Using the GPU Cloud

  The article examines the pros and cons of building an on-premise GPU machine versus using a GPU cloud service for projects involving deep learning and artificial intelligence, analyzing factors like cost, performance, operations, and scalability.

  https://www.kdnuggets.com/building-a-gpu-machine-vs-using-the-gpu-cloud

• Top 10 AI Startups to Work for in India

  Want to jumpstart your career in AI? Discover the top 10 trailblazing Indian startups that are reshaping industries with cutting-edge innovation and providing unparalleled opportunities to work on impactful projects.

  https://www.kdnuggets.com/top-10-ai-startups-to-work-for-in-india

• 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

• Data Scientists Need to Specialize to Survive the Tech Winter

  In this article, I explore the benefits of specialization for data scientists. Drawing on my own experience as a data scientist, I argue that specializing in a specific area can help you stand out in a crowded job market and provide you with more fulfilling career opportunities.

  https://www.kdnuggets.com/2023/08/data-scientists-need-specialize-survive-tech-winter.html

• Baby AGI: The Birth of a Fully Autonomous AI

  Introducing the new fully autonomous task manager that can create, track and prioritize your company's projects using artificial intelligence.

  https://www.kdnuggets.com/2023/04/baby-agi-birth-fully-autonomous-ai.html

• Why SQL Will Remain the Data Scientist’s Best Friend

  Machine learning, big data analytics or AI may steal the headlines, but if you want to hone a smart, strategic skill that can elevate your career, look no further than SQL.

  https://www.kdnuggets.com/2022/07/sql-remain-data-scientist-best-friend.html

• Prioritizing Data Science Models for Production

  Statistical performance metrics aren’t enough to pick the right models to bring to market.

  https://www.kdnuggets.com/2022/04/prioritizing-data-science-models-production.html

• MLOps Is a Mess But That’s to be Expected

  In this post, I want to focus the discussion about the state of machine learning operations (MLOps) today, where we are, where we are going.

  https://www.kdnuggets.com/2022/03/mlops-mess-expected.html

• Data Labeling for Machine Learning: Market Overview, Approaches, and Tools

  So much of data science and machine learning is founded on having clean and well-understood data sources that it is unsurprising that the data labeling market is growing faster than ever. Here, we highlight many of the top players in this industry and the techniques they use to help you consider which might make a good partner for your needs.

  https://www.kdnuggets.com/2021/12/data-labeling-ml-overview-and-tools.html

• 7 of The Coolest Machine Learning Topics of 2021 at ODSC West

  At our upcoming event this November 16th-18th in San Francisco, ODSC West 2021 will feature a plethora of talks, workshops, and training sessions on machine learning topics, deep learning, NLP, MLOps, and so on. You can register now for 20% off all ticket types, or register for a free AI Expo Pass to see what some big names in AI are doing now.

  https://www.kdnuggets.com/2021/11/odsc-7-coolest-machine-learning-topics.html

• How to pitch to VCs, explained: The Deck We Used to Raise Capital For Our Open-Source ELT Platform

  Winning seed funding from venture capitalists is a daunting task, and the pitch is key. Learn how one effective slide deck resulted in a successful early funding round for an open-source start-up, Airbyte.

  https://www.kdnuggets.com/2021/05/vc-pitch-deck-open-source-elt-platform.html

• Machine learning is going real-time

  Extracting immediate predictions from machine learning algorithms on the spot based on brand-new data can offer a next level of interaction and potential value to its consumers. The infrastructure and tech stack required to implement such real-time systems is also next level, and many organizations -- especially in the US -- seem to be resisting. But, what even is real-time ML, and how can it deliver a better experience?

  https://www.kdnuggets.com/2021/01/machine-learning-real-time.html

• Main 2020 Developments and Key 2021 Trends in AI, Data Science, Machine Learning Technology">Main 2020 Developments and Key 2021 Trends in AI, Data Science, Machine Learning Technology

  Our panel of leading experts reviews 2020 main developments and examines the key trends in AI, Data Science, Machine Learning, and Deep Learning Technology.

  https://www.kdnuggets.com/2020/12/developments-trends-ai-data-science-machine-learning-technology.html

• Compute Goes Brrr: Revisiting Sutton’s Bitter Lesson for AI

  "It's just about having more compute." Wait, is that really all there is to AI? As Richard Sutton's 'bitter lesson' sinks in for more AI researchers, a debate has stirred that considers a potentially more subtle relationship between advancements in AI based on ever-more-clever algorithms and massively scaled computational power.

  https://www.kdnuggets.com/2020/11/revisiting-sutton-bitter-lesson-ai.html

• Goodhart’s Law for Data Science and what happens when a measure becomes a target?">Goodhart’s Law for Data Science and what happens when a measure becomes a target?

  When developing analytics and algorithms to better understand a business target, unintended biases can sneak in that ensure desired outcomes are obtained. Guiding your work with multiple metrics in mind can help avoid such consequences of Goodhart's Law.

  https://www.kdnuggets.com/2020/10/goodharts-law-data-science-measure-target.html

• What I learned from looking at 200 machine learning tools

  While hundreds of machine learning tools are available today, the ML software landscape may still be underdeveloped with more room to mature. This review considers the state of ML tools, existing challenges, and which frameworks are addressing the future of machine learning software.

  https://www.kdnuggets.com/2020/07/200-machine-learning-tools.html

• 20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 2)">20 AI, Data Science, Machine Learning Terms You Need to Know in 2020 (Part 2)

  We explain important AI, ML, Data Science terms you should know in 2020, including Double Descent, Ethics in AI, Explainability (Explainable AI), Full Stack Data Science, Geospatial, GPT-2, NLG (Natural Language Generation), PyTorch, Reinforcement Learning, and Transformer Architecture.

  https://www.kdnuggets.com/2020/03/ai-data-science-machine-learning-key-terms-part2.html

• A Non-Technical Reading List for Data Science">A Non-Technical Reading List for Data Science

  The world still cannot be reduced to numbers on a page because human beings are still the ones making all the decisions. So, the best data scientists understand the numbers and the people. Check out these great data science books that will make you a better data scientist without delving into the technical details.

  https://www.kdnuggets.com/2019/12/non-technical-reading-list-data-science.html

• 10 Free Must-read Books on AI">10 Free Must-read Books on AI

  Artificial Intelligence continues to fill the media headlines while scientists and engineers rapidly expand its capabilities and applications. With such explosive growth in the field, there is a great deal to learn. Dive into these 10 free books that are must-reads to support your AI study and work.

  https://www.kdnuggets.com/2019/11/10-free-must-read-books-ai.html

• How AI will transform healthcare (and can it fix the US healthcare system?)">How AI will transform healthcare (and can it fix the US healthcare system?)

  This thorough review focuses on the impact of AI, 5G, and edge computing on the healthcare sector in the 2020s as well as a look at quantum computing's potential impact on AI, healthcare, and financial services.

  https://www.kdnuggets.com/2019/09/ai-transform-healthcare.html

• The Death of Big Data and the Emergence of the Multi-Cloud Era">The Death of Big Data and the Emergence of the Multi-Cloud Era

  The Era of Big Data is coming to an end as the focus shifts from how we collect data to processing that data in real-time. Big Data is now a business asset supporting the next eras of multi-cloud support, machine learning, and real-time analytics.

  https://www.kdnuggets.com/2019/07/death-big-data-multi-cloud-era.html

• Linear Programming and Discrete Optimization with Python using PuLP

  Knowledge of such optimization techniques is extremely useful for data scientists and machine learning (ML) practitioners as discrete and continuous optimization lie at the heart of modern ML and AI systems as well as data-driven business analytics processes.

  https://www.kdnuggets.com/2019/05/linear-programming-discrete-optimization-python-pulp.html

• Diversity in Data Science: Overview and Strategy

  We take a hard look at diversity within the tech industry, root causes, and potential solutions and highlight resources/initiatives that can connect readers with programs aiding their professional development.

  https://www.kdnuggets.com/2018/09/diversity-data-science.html

• Advice For Applying To Data Science Jobs

  A comprehensive guide to applying for a job in data science, covering the application, interview and offer stage.

  https://www.kdnuggets.com/2018/06/advice-applying-data-science-jobs.html

• To Kaggle Or Not

  Kaggle is the most well known competition platform for predictive modeling and analytics. This article looks into the different aspects of Kaggle and the benefits it can bring to data scientists.

  https://www.kdnuggets.com/2018/05/to-kaggle-or-not.html

• Want to Become a Data Scientist? Try Feynman Technique">Want to Become a Data Scientist? Try Feynman Technique

  Get over the impostor syndrome by developing a strong understanding about the various Data Science topics using the Feynman Technique

  https://www.kdnuggets.com/2018/01/data-scientist-feynman-technique.html

• Data Science, Machine Learning: Main Developments in 2017 and Key Trends in 2018">Data Science, Machine Learning: Main Developments in 2017 and Key Trends in 2018

  The leading experts in the field on the main Data Science, Machine Learning, Predictive Analytics developments in 2017 and key trends in 2018.

  https://www.kdnuggets.com/2017/12/data-science-machine-learning-main-developments-trends.html

• Statistical Mistakes Even Scientists Make

  Scientists are all experts in statistics, right? Wrong.

  https://www.kdnuggets.com/2017/10/statistical-mistakes-even-scientists-make.html

• What Artificial Intelligence and Machine Learning Can Do—And What It Can’t">What Artificial Intelligence and Machine Learning Can Do—And What It Can’t

  I have seen situations where AI (or at least machine learning) had an incredible impact on a business—I also have seen situations where this was not the case. So, what was the difference?

  https://www.kdnuggets.com/2017/08/rapidminer-ai-machine-learning-can-do.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

• The Evolution of a Productive Data Team

  Successful data teams at companies of any size are able to produce results because they develop gradually through a series of stages and acquire skills along the way that help them stay efficient and effective.

  https://www.kdnuggets.com/2017/04/dataiku-evolution-productive-data-team.html

• A Brief History of Artificial Intelligence">A Brief History of Artificial Intelligence

  This post is a brief outline of what happened in artificial intelligence in the last 60 years. A great place to start or brush up on your history.
   
   

  https://www.kdnuggets.com/2017/04/brief-history-artificial-intelligence.html

• 50 Companies Leading The AI Revolution, Detailed">50 Companies Leading The AI Revolution, Detailed

  We detail 50 companies leading the Artificial Intelligence revolution in AD Sales, CRM, Autotech, Business Intelligence and analytics, Commerce, Conversational AI/Bots, Core AI, Cyber-Security, Fintech, Healthcare, IoT, Vision, and other areas.

  https://www.kdnuggets.com/2017/03/50-companies-leading-ai-revolution-detailed.html

• 17 More Must-Know Data Science Interview Questions and Answers, Part 3">17 More Must-Know Data Science Interview Questions and Answers, Part 3

  The third and final part of 17 new must-know Data Science interview questions and answers covers A/B testing, data visualization, Twitter influence evaluation, and Big Data quality.
   
   

  https://www.kdnuggets.com/2017/03/17-data-science-interview-questions-answers-part-3.html

• The Current State of Automated Machine Learning

  What is automated machine learning (AutoML)? Why do we need it? What are some of the AutoML tools that are available? What does its future hold? Read this article for answers to these and other AutoML questions.

  https://www.kdnuggets.com/2017/01/current-state-automated-machine-learning.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

• The big data ecosystem for science: Climate Science and Climate Change

  Climate change is one of the most pressing challenges for human society in the 21st century. We review the Big Data ecosystem for studying the climate change.

  https://www.kdnuggets.com/2016/12/big-data-ecosystem-science-climate-change.html

• Don’t Buy Machine Learning

  In many projects, the amount of effort spent on R&D on Machine Learning is usually a small fraction of the total effort, or it’s not even there because we plan it for a future phase after building the application first.

  https://www.kdnuggets.com/2016/03/dont-buy-machine-learning.html

• Big Data and Data Science for Security and Fraud Detection

  We review big data analytics tools and technologies that combine text mining, machine learning and network analysis for security threat prediction, detection and prevention at an early stage.

  https://www.kdnuggets.com/2015/12/big-data-science-security-fraud-detection.html

• KDnuggets™ News 14:n22, Aug 20

  Features | News | Opinions | Interviews | Webcasts | Courses | Meetings | Jobs | Publications | Tweets | Quote Features Four main languages Read more »

  https://www.kdnuggets.com/2014/n22.html

• Stacking the Deck: The Next Wave of Opportunity in Big Data

  A leading venture capitalist explains why Big Data infrastructure market is mostly mature and where lies the next big area of opportunities related to Big Data.

  https://www.kdnuggets.com/2014/05/stacking-deck-next-wave-opportunity-big-data.html

• 2013 Nov News: Analytics, Big Data, Data Mining and Data Science Features, News, Software

  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/news-software.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

• 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

• Is Data Science The End of Statistics? A Discussion

  Here is an interesting discussion on LinkedIn, started by a provocative post "Data Science: The End of Statistics?" What is the relationship between Data Science and Statistics and in what sense are "Statistics" ending?

  https://www.kdnuggets.com/2013/04/data-science-end-statistics-discussion.html

• KDnuggets™ News 13:n18, Jul 31

  Features (8) | Software (4) | Webcasts (2) | Courses, Events (5) | Meetings (1) | Jobs (14) | Academic (2) | Competitions (2) | Publications Read more »

  https://www.kdnuggets.com/2013/n18.html

• KDnuggets™ News 13:n17, July 17

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

  https://www.kdnuggets.com/2013/n17.html