Goto

Collaborating Authors

Machine Learning


GitHub - kandarpkakkad/Machine-Learning-A-to-Z: Machine Learning A-Z (Udemy)

#artificialintelligence

The objective of this course is to learn Machine Learning concepts and be handy with coding of machine learning. Here I have the solutions and codes of "Machine Learning A to Z" course of Udemy.


Top 10 AI graduate degree programs

#artificialintelligence

Artificial Intelligence (AI) is a fast-growing and evolving field, and data scientists with AI skills are in high demand. The field requires broad training involving principles of computer science, cognitive psychology, and engineering. If you want to grow your data scientist career and capitalize on the demand for the role, you might consider getting a graduate degree in AI. U.S. News & World Report ranks the best AI graduate programs at computer science schools based on surveys sent to academic officials in fall 2021 and early 2022. Here are the top 10 programs that made the list as having the best AI graduate programs in the US.


The 6 Python Machine Learning Tools Every Data Scientist Should Know About - KDnuggets

#artificialintelligence

Machine learning is rapidly evolving and the crucial focus of the software development industry. The infusion of artificial intelligence with machine learning has been a game-changer. More and more businesses are focusing on wide-scale research and implementation of this domain. Machine learning provides enormous advantages. It can quickly identify patterns and trends and the concept of automation comes to reality through ML.


Classify small images accurately using little memory and CPU with ImageSig

#artificialintelligence

Classify small images accurately using little memory and CPU with ImageSig ImageSig: A signature transform for ultra-lightweight image recognition arXiv paper abstract https://arxiv.org/abs/2205.06929v1 arXiv PDF paper https://arxiv.org/pdf/2205.06929v1.pdf This paper introduces a new lightweight method for image recognition. ImageSig is based on computing signatures and does not require a convolutional structure or an attention-based encoder. ... achieves: a) an accuracy for 64 X 64 RGB images


The role of AI and machine learning in revolutionizing clinical research - MedCity News

#artificialintelligence

Advanced technologies such as artificial intelligence (AI), machine learning (ML), and natural language processing (NLP) have become a cornerstone of successful modern clinical trials, integrated into many of the technologies enabling the transformation of clinical development. The health and life sciences industry's dramatic leap forward into the digital age in recent years has been a game-changer with innovations and scientific breakthroughs that are improving patient outcomes and population health. Consequently, embracing digital transformation is no longer an option but an industry standard. Let's explore what that truly means for clinical development. Over the years, technology has equipped clinical leaders to successfully reduce costs while accelerating stages of research and development.


Unleashing the power of machine learning models in banking through explainable artificial intelligence (XAI)

#artificialintelligence

The "black-box" conundrum is one of the biggest roadblocks preventing banks from executing their artificial intelligence (AI) strategies. It's easy to see why: Picture a large bank known for its technology prowess designing a new neural network model that predicts creditworthiness among the underserved community more accurately than any other algorithm in the marketplace. This model processes dozens of variables as inputs, including never-before-used alternative data. The developers are thrilled, senior management is happy that they can expand their services to the underserved market, and business executives believe they now have a competitive differentiator. But there is one pesky problem: The developers who built the model cannot explain how it arrives at the credit outcomes, let alone identify which factors had the biggest influence on them.


For AI model success, utilize MLops and get the data right

#artificialintelligence

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. It's critical to adopt a data-centric mindset and support it with ML operations Artificial intelligence (AI) in the lab is one thing; in the real world, it's another. Many AI models fail to yield reliable results when deployed. Others start well, but then results erode, leaving their owners frustrated. Many businesses do not get the return on AI they expect. Why do AI models fail and what is the remedy?


Exciting Data Science Project Ideas To Brush Up Your Skills

#artificialintelligence

Projects have always been thought of as measurable improvements resulting from a result produced, which serve as the icing on the cake for achieving personal or corporate goals. Talking about individual projects, have you found it challenging to learn at home? Many of us are in the same boat -- there are far too many things to handle during these trying times, and learning has taken a back seat, contrary to our expectations. So, what are our options for getting back on track? How can we apply what we have learned about data science in the real world? Picking an open-source data science project and sticking with it is extremely beneficial.


ML Tools to Accelerate your work with Cassie Breviu

#artificialintelligence

Want to ensure your app developers can create secure and smooth login experiences for your customers? With Curity you can protect user identities, secure apps and websites, and manage API access. Welcome to the InfoQ podcast. My name is Roland Meertens and today, I am interviewing Cassie Breviu. She is a senior program manager at Microsoft and hosted the innovations in machine learning systems track at QCon London. I am actually speaking to her in person at the venue of QCon London Conference. In this interview, I will talk with her on how she got started with AI and what machine learning tools can accelerate your work when deploying models on a wide range of devices. We will also talk about GitHub Copilot and how AI can help you be a better programmer. If you want to see her talk on how to operationalize transformer models on the edge, at the moment of recording this, you can still register for the QCon Plus Conference or see if the recording is already uploaded on infoq.com. Welcome, Cassie to QCon London. I'm very glad to see you here. I hope you're happy to be at this conference. I heard that you actually got into AI by being at the conference. I am thoroughly enjoying this conference. It's really put together really well and I really enjoy it. So what happened was I was at a developer conference. I was a full stack C# engineer and I'd always been really interested in AI and machine learning, but it always seemed scary and out of reach. I had even tried to read some books on it and I thought, "Well, this might be just too much for me or too complicated or I just can't do this." So I went to this talk by Jennifer Marsman and she did this amazing talk on, Would You Survive the Titanic Sinking? She used this product that's called Azure Machine Learning Designer.


Are There a Lot of Artificial Intelligence (A.I.) Jobs Right Now?

#artificialintelligence

A new breakdown shows that A.I. remains a highly specialized field with relatively few job openings--but that will almost certainly change in coming years. CompTIA's monthly Tech Jobs Report reveals that states with the largest tech hubs--including California, Texas, Washington, and Massachusetts--lead when it comes to A.I.-related job postings. It's true that companies don't need nearly as many machine-learning experts as, say, software developers or data scientists. Smaller organizations might not even have the budget to fill out an A.I. division. But CompTIA's job numbers keep growing month after month, indicating a sustained appetite for A.I. talent, especially among larger companies with the money to actually afford researchers and specialists.