Hope all is going well. So, after receiving a great response ( and some really good feedback and inputs) for 60 days of Data Science and ML with projects series, I'm excited to share that I'm starting a new Series -- 30 days of Machine Learning Ops with (amazing) projects. PS: I'll be writing as and when I'm free out of my busy…

Artist and musician Zach Katz virtually transforms the streets of the world's major cities in order to show how the space could be made more hospitable to pedestrians. Every day, he posts new creations on his Twitter account and, in the space of a few weeks, has become something of a star among Internet users, city planners and politicians. How do we imagine the downtown zones of the future? The Twitter account @Betterstreetsai explores this question by using DALL-E, the artificial intelligence (AI) that has started a real trend on the Web. Here, fountains, green space, rails or even roads reserved for bikes and cyclists take over the space to dramatically change the urban landscape.

Role requiring'No experience data provided' months of experience in Los Angeles We know that there are all kinds of Data Scientists, with varying levels of knowledge about different platforms and data sources. At Rower, we're more interested in candidates who are hard-working, smart and love what they do. We care more about overall database and analytical skills rather than experience with a certain database platform. We only ask that you have a strong understanding of Python and SQL as a whole and can apply your skills within our fast paced and agile approach. BASIC QUALFICATIONS AND EDUCATION: • Ability to easily code with Base Python (List, Dictionary, Tuple, For Loops, Functions) • Proficient with applied data science with Python including forecasting, casual modeling, and natural language processing. Founded on years of business consulting experience and a culture of complete client satisfaction, Rower delivers the absolute best in full-spectrum IT and data solutions.

Experience with Spark or Hadoop is nice to have. Experience with React/Node is nice to have.

Is mankind really on the brink of an exciting, but potentially terrifying future? Some scholars think that this is the case say, but they base their prediction not on what is currently happening in universities and robotics laboratories around the world, but on their belief that a robotic revolution has already taken place. Ancient religions and myths spoke of many artificially constructed entities. They are often depicted as instruments of protection, but it sometimes happens that they rebel against those who created them with disastrous consequences. American Rabbi Ariel Bar Tzadok, founder of the Kosher Torah School, stated: "There is a legend that has existed since the dawn of time. I am referring to the Golem. It is an artificial life source from inanimate material that then comes to life. The Golem was created by means of an ancient technology known to the Pharaoh's magicians, Moses, the rabbis of the Talmud and the rabbis of the Kabbalah in Europe" They all brought the Golem to life through magic by writing the name of God on the creature's forehead.

Deep learning is the subfield of machine learning which is employed to execute complicated tasks similar as speech recognition, textbook bracket, etc. Any deep learning model tries to generalize the data employing an algorithm and tries to frame forecasts on the unseen data. The most common system supporting multiple of the deep learning model training channels is grade descent. But vanilla grade descent can chance several problems, like picking up stuck at local minima or the problems of going off and dematerializing grades. To situate these problems several variants of the grade descent have been contrived over occasion.

Machine learning algorithms can, for example, spit out molecule combinations in the hunt for new drugs, map out schematics for novel chip designs, and even write code. She said Google had filed multiple patents describing a machine-learning technique used internally to automatically design and map out components in the company's custom AI accelerator TPU chips currently used in its servers. The uncertainty surrounding whether it's possible or how best to apply for patents protecting IP produced by algorithms can sometimes be a roadblock in developing new products, especially in the pharmaceutical and biotech industries. Companies that rely on using AI software to create new drugs or antibodies, for example, often need to secure patents before they can kick start clinical trials. "We at Google are definitely giving a lot of thought to the inventorship question overall… We're thinking through inventive contribution issues throughout the AI development process," Sheridan concluded.

Machine learning is an increasingly popular tool of scientific research, but a lot of the scientists using it might not really know what they're doing.

When Sodexo, a company that operates over 400 university dining programs, was looking for a futuristic, seamless experience to provide students in place of the usual buffet meal options, it wasn't necessarily thinking of AI and computer vision. The only thing the corporation knew was that they wanted to build shop-and-go platforms, a.k.a shops with no cashiers, similar to Amazon Go. That is a store where customers may stroll in, choose products off the shelves, and leave without waiting in line at the register or swiping a code at a self-checkout. "Students today want things they can partially or fully prepare in their room or apartment, with organic, highly-local options. We also wanted to remove friction, but many solutions still require the interaction of the guest with a cashier – this generation really doesn't want to talk to a lot of people in their service interactions," said Kevin Rettle, global vice president of product development and digital innovation at Sodexo.

Could artificial intelligence (AI) enhance the ability of clinicians to detect prediabetes and diabetes? Findings from a recently published study show that adjunctive use of DiaBeats, a machine learning-based algorithm, with electrocardiogram (ECG) recordings may provide an alternative noninvasive imaging approach to screening for prediabetes and diabetes. "In theory, our study provides a relatively inexpensive, non-invasive, and accurate alternative (to current diagnostic methods) which can be used as a gatekeeper to effectively detect diabetes and prediabetes early in its course," wrote study co-author Anoop R. Kulkarni, Ph.D., who is affiliated with Innotomy Consulting in Bengaluru, India, anbd colleagues. "Nevertheless, adoption of this algorithm into routine practice will need robust validation on external, independent data sets." As the intrinsic risk of prediabetes has become increasingly recognized by the medical community, identification of low-cost, noninvasive methods for diagnosis or risk stratification for prediabetes and future diabetes has become paramount.