Highlights: Welcome back to the all-new series on Machine Learning. In the previous post, we gave you a sneak peak into the basics of Machine Learning, the two types of Machine Learning, viz., Supervised & Unsupervised, and implemented some examples using various algorithms in each of the techniques. In this new tutorial post, we will explore one of the most widely used Supervised Learning algorithms in the world today – Linear Regression. We will start off with some theory and go on to build a simple model in Python, from scratch. In our previous post (also the first post of this Machine Learning tutorial series), we brushed the fundamentals of Linear Regression using the example of housing price prediction, given the size of the house. If you remember, the prediction was based on the linear relationship that existed between the house price and the size of the house. Have a look at the image below. In the graph above, the size of the house is shown along the horizontal axis and the price of a house is shown along the vertical axis. Here, each data point is a house with its respective size and the price that the house was recently sold for.

The printed version of GPT-3 book is here, and it feels *SO* rewarding to hold it in my hands! 1 year of my and Shubham's work materialised in a sleek white book with a West African giraffe cover. It's been quite a journey filled with sleepless nights, brainstorming sessions, and countless revisions. I kept thinking how fortunate I am to be able to explore the most exciting artificial intelligence ecosystem in the format of O'Reilly book. I hope it will become a useful resource to the NLP community. If you want to get up to speed with the latest and greatest NLP (no matter your background!), this book is for you! Massive thank you to everyone who helped make this book possible.

If you are a student or professional interested in the latest trends in the computing world, you would have heard of terms like artificial intelligence, data science, machine learning, deep learning, etc. The first article in this series on artificial intelligence explains these terms, and sets the platform for a simple tutorial that will help beginners get started with AI. Today it is absolutely necessary for any student or professional in the field of computer science to learn at least the basics of AI, data science, machine learning and deep learning. However, where does one begin to do so? To answer this question, I have gone through a number of textbooks and tutorials that teach AI. Some start at a theoretical level (a lot of maths), some teach you AI in a language-agnostic way (they don't care whether you know C, C, Java, Python, or some other programming language), and yet others assume you are an expert in linear algebra, probability, statistics, etc. In my opinion, all of them are useful to a great extent. But the important question remains -- where should an absolute beginner interested in AI begin his or her journey? Frankly, there are many fine ways to begin your AI journey.

RALEIGH, NC / ACCESSWIRE / August 8, 2022 / 919 Marketing, one of the nation's fastest-growing content marketing agencies, announces the acquisition of ClickCulture, a Raleigh, N.C. -based award-winning web development and digital marketing company. This is the third acquisition by 919 Marketing to boldly expand its roster of technology-focused marketing services to become the full-service marketing leader for emerging and mature franchise brands and non-profit companies. "This exciting new partnership with the team at ClickCulture expands our company to give us more creative firepower and a deeper bench of talent to better serve our clients", says David Chapman, CEO, and founder of 919 Marketing. "We can now elevate our creative capabilities to include custom applications for websites, unique digital campaigns, and elite, award-winning graphic design to help our clients attract more customers and grow their businesses. We have a lot of smart people doing great work and now we have the data-driven creative capabilities needed to truly dominate as the holistic, one-stop solution for nonprofit companies and multi-location and franchise brands."

Machine learning and AI continue to reach further into IT services and complement applications developed by software engineers. IT teams need to sharpen their machine learning skills if they want to keep up. Cloud computing services support an array of functionality needed to build and deploy AI and machine learning applications. In many ways, AI systems are managed much like other software that IT pros are familiar with in the cloud. But just because someone can deploy an application, that does not necessarily mean they can successfully deploy a machine learning model.

Ivanti's platform makes it possible for employees to stay productive, secure and engaged wherever they are. With headquarters in Utah, offices in London and Paris and nearly 3,200 employees in 25 countries around the world, we are the Everywhere Workplace – it's a great time to work for Ivanti! We anticipate our customers' needs, we are highly responsive, and we deliver innovative solutions that exceed their expectations. Our mission is to be a global technology leader enabling organizations to thrive in the Everywhere Workplace – automating the tasks that discover, manage, secure and service all of their IT assets. Teamwork is intrinsic to what we do and why we do it.

Find open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general, filtered by job title or popular skill, toolset and products used.

Onto is Europe's largest electric car subscription service, growing at over 20% month on month, with over 5,500 subscribers today, we're looking to at least double our customers in 2022. We are a high-growth tech scale-up, having launched 4 years ago with significant funding from top-tier VCs, most recently raising £125 million of equity and debt in July 2021 through a Series B funding round. Our team has grown dramatically, with offices in London and Leamington and with overseas expansion planned for 2022. We're an open and collaborative bunch who care deeply about creating an amazing team for each and every person to work in. We understand the best way to create a product that our customers love is to create a team in which people love working.

Find open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general, filtered by job title or popular skill, toolset and products used.

Artificial intelligence (AI) is the ability of machines to mimic human capabilities in a way that we would consider'smart'. You most likely have come across – or are aware of – AI applications such as self-driving cars, facial recognition, chess or go players, security systems, or speech/voice recognition (for example, those used in an intelligent virtual assistant). In conventional computing, a programmer writes a computer program that precisely instructs a computer what to do to solve a particular problem. With AI, however, the programmer instead writes a program that allows the computer to learn to solve a problem by itself. That sounds like overdoing it, but this is really the way we do things.