If you are looking for an answer to the question What is Artificial Intelligence? and you only have a minute, then here's the definition the Association for the Advancement of Artificial Intelligence offers on its home page: "the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines."
However, if you are fortunate enough to have more than a minute, then please get ready to embark upon an exciting journey exploring AI (but beware, it could last a lifetime) …
Machine Learning in Python: Principal Component Analysis (PCA) for Handling High-Dimensional Data In this video, I will be showing you how to perform principal component analysis (PCA) in Python using the scikit-learn package. PCA represents a powerful learning approach that enables the analysis of high-dimensional data as well as reveal the contribution of descriptors in governing the distribution of data clusters. Particularly, we will be creating PCA scree plot, scores plot and loadings plot. This video is part of the [Python Data Science Project] series. If you're new here, it would mean the world to me if you would consider subscribing to this channel.
Google Brain had recently launched the TensorFlow Developer Certificate program which would enable machine learning (ML) enthusiasts to demonstrate their skills in using TensorFlow to solve deep learning and ML problems. According to the blog post, the goal of this certificate is to provide them with the opportunity to showcase their expertise in ML in an increasingly AI-driven job market. TensorFlow is one of the popular open-source libraries in ML which provides a suitable abode with essential tools for ML researchers and developers to perform SOTA ML applications. The developers at Google Brain claim that this is intended as a foundational certificate for students, developers, and data scientists who want to demonstrate practical ML skills through building and training of models using TensorFlow. Currently, this is a level one certificate exam which tests a developer's foundational knowledge of integrating ML into tools and applications.
Machine learning (ML) practitioners gather data, design algorithms, run experiments, and evaluate the results. After you create an ML model, you face another problem: serving predictions at scale cost-effectively. Serverless technology empowers you to serve your model predictions without worrying about how to manage the underlying infrastructure. Services like AWS Lambda only charge for the amount of time that you run your code, which allows for significant cost savings. Depending on latency and memory requirements, AWS Lambda can be an excellent choice for easily deploying ML models.
Topic "Taking the complexity out of Machine Learning with Microsoft Azure Machine Learning studio" Microsoft Azure Machine Learning Studio is a collaborative, drag-and-drop tool you can use to build, test, and deploy predictive analytics solutions on your data. Azure Machine Learning Studio publishes models as web services that can easily be consumed by custom apps or BI tools such as Excel. Demo: importing a data set in to Azure Machine Learning Studio and publish the model as web services. Bio Frank Falvey is an Azure Cloud Advocate, working in Dell Technologies and based in Cork, loves problem solving or sharing his knowledge with people.
I joined Infosys in June of 2019. The reason I came here is that we have the unique intersection of being able to build an executable strategy. Many services firms love to do strategy work and then fail at execution. Some are great at execution but make everything about price. What drew me to Infosys is that we make it about realized value.
What's dangerous is not to evolve. The darling of consumers and investors alike, Mr. Bezos sure seems to have the future figured out. Amazon today is the most AI driven customer experience platform in the world, besides just being an e-commerce marketplace. Retail has moved from the brick-and-mortar store front to beautiful and highly aesthetic web portals, accessible on any device you use, that seem, at times, shockingly intuitive. The secret ingredient here is AI.
In 2016, Seattle-based startup Turi was helping almost 100 customers create and manage software that uses machine learning, a powerful type of artificial intelligence. Its technology was so promising that Apple Inc. snapped it up for $200 million. The deal was a triumph for investors and founders, but one backer thought Turi -- and the broader tech industry -- might be better off if the startup had spurned Apple's advances. Matt McIlwain, managing director at Madrona Venture Group, said it's important that at least some emerging tech businesses remain independent, rather than falling into the arms of Apple, Amazon.com "It is economically beneficial to society to have more stand-alone, independent companies. We generally think that's better than just having these companies consolidated into larger ones," McIlwain said.
United Arab Emirates-based global EdTech Alef Education is on a mission to digitally transform the education sector to support its most valuable resource: teachers. The United Nations Educational, Scientific, and Cultural Organization (UNESCO) Institute for Statistics estimates that the world needs almost 69 million new teachers by 2030 to meet the deadline of the United Nations Sustainable Development Goal for quality education. But according to latest projections, the world will fail its education commitments without addressing the teacher shortage. Overwhelming teacher workload is a major contributor to teacher scarcity and the urgency to tackle this imbalance is a key driver for United Arab Emirates (UAE)-based global education technology Alef Education. The forward-thinking organization is shrinking teacher workloads and helping them better manage classrooms through its artificial intelligence (AI)-powered platform built on Amazon Web Services (AWS).
Machine Learning in Python: Building a Linear Regression Model In this video, I will be showing you how to build a linear regression model in Python using the scikit-learn package. We will be using the Diabetes dataset (built-in data from scikit-learn) and the Boston Housing (download from GitHub) dataset. This video is part of the [Python Data Science Project] series. If you're new here, it would mean the world to me if you would consider subscribing to this channel. Disclaimer: Chanin is a participant in the Amazon Services LLC Associates Program, an affiliate advertising program designed to provide a means for sites to earn advertising fees by advertising and linking to http://www.amazon.com.
Artificial Intelligence (AI) also known as machine learning has come a long way in the recent few years. Instead of being a subject of discussion, it has become a reality. There has been ready integration of AI across a large number of industries. This has given rise to several AI development companies across the world. These AI consulting firms offer services to their clients and help with the integration of AI in their operations.