Members-only Machine Learning Supervised vs. unsupervised learning 101: Key differences and applications We will explore the concepts of supervised and unsupervised learning and highlight their key differences....
Members-only Challenges of regulating generative AI in the European Union Explore the challenges in EU's GenAI regulation and the AI Safety Act's impact, as EU struggles to define effective AI governance measures....
Members-only Artificial Intelligence AI’s influence and the future of privacy How can companies educate the consumer about the benefits and pitfalls of AI whilst continually innovating their practices?...
Members-only Artificial Intelligence Unlocking the future of AI: OpenAI’s game-changing developer conference Under the vision of OpenAI’s CEO, the conference showcased innovations designed to make AI more accessible, powerful, and customizable....
Members-only Artificial Intelligence How to leverage AI in finance with Christian Martinez Our sister community, Finance Alliance, recently held an Ask Me Anything (AMA) session with Christian Martinez, Finance Manager at Kraft Heinz....
Members-only Generative AI Why companies aren't using generative AI In this article, we’ll deep-dive into the reasons why companies aren’t using generative AI...
Members-only Summits Integrating LLMs into business operations | Q&A with Shakudo Ahead of Computer Vision Summit Boston, we spoke with Yevgeniy Vahlis from Shakudo to find out more what you can expect from this expert discussion....
Members-only Generative AI Cost saving is not a leading driver of generative AI adoption We surveyed companies about the drivers behind the adoption of generative AI. Surprisingly, cost savings weren't a leading factor....
Members-only Membership content Combining computer vision and language models to create intelligent applications In this session, I'm going to talk about when you bring language models and computer vision together, and what the possibilities are in the AI domain....
Members-only Generative AI A third of Generative AI users worry about biases and errors Biases, errors, and limitations of generative AI were highlighted as the main concerns when using the technology....
Members-only Generative AI The 5 primary generative AI applications (and how they work) According to our Generative AI Report, text applications are at the top of the reasons for the adoption of generative AI tools (40.8%)....
Members-only Generative AI The future of digital transformation Explore the magic of digital transformation through Generative AI, real-world use cases, and future prospects like low/no-code platforms....
Members-only Generative AI Download the Generative AI 2023 report today The Generative AI 2023 report highlights the ‘why’ and the ‘why not’ of generative AI adoption, alongside a variety of surprising statistics....
Members-only Understanding the bias-variance tradeoff in machine learning Whenever we speak about model prediction, it is essential to comprehend prediction errors (bias and variance). There is a tradeoff between a model’...
Members-only Machine Learning Boosting and bagging: Powerful ensemble methods in machine learning While working on a classification problem, a regression analysis, or another data science project, bagging, and boosting algorithms can play a vital role....
