In this paper we consider generalized classes of potentially non-monotone risk functions for use as evaluation metrics in learning tasks. The resulting risks are in general non-convex and non-smooth, which makes both the computational and inferential sides of the learning problem difficult. For random losses belonging to any Banach space, we obtain sufficient conditions for the risk functions to be weakly convex, and to admit unbiased stochastic directional derivatives. We then use recent work on stochastic optimization of weakly convex functionals to obtain non-asymptotic guarantees of near-stationarity for Hilbert hypothesis classes, under assumptions that are weak enough to capture a wide variety of feedback distributions, including potentially heavy-tailed losses and gradients.

Offered by DeepLearning.AI. About TensorFlow TensorFlow is an end-to-end open-source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML, and developers easily build and deploy ML-powered applications. TensorFlow is commonly used for machine learning applications such as voice recognition and detection, Google Translate, image recognition, and natural language processing. About this Specialization Expand your knowledge of the Functional API and build exotic non-sequential model types. Learn how to optimize training in different environments with multiple processors and chip types and get introduced to advanced computer vision scenarios such as object detection, image segmentation, and interpreting convolutions. Explore generative deep learning including the ways AIs can create new content from Style Transfer to Auto Encoding, VAEs, and GANs. About you This Specialization is for software and machine learning engineers with a foundational understanding of TensorFlow who are looking to expand their knowledge and skill set by learning advanced TensorFlow features to build powerful models. Looking for a place to start? Master foundational basics with the DeepLearning.AI TensorFlow Developer Professional Certificate. Ready to deploy your models to the world? Learn how to go live with the TensorFlow: Data and Deployment Specialization.

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The demand for Data Scientists is immense. In this course, you'll learn how you can play a part in fulfilling this demand and build a long, successful career for yourself. The #1 goal of this course is clear: give you all the skills you need to be a Data Scientist who could start the job tomorrow... within 6 weeks. With so much ground to cover, we've stripped out the fluff and geared the lessons to focus 100% on preparing you as a Data Scientist. You'll pick up all the core concepts that veteran Data Scientists understand intimately.

Way back in 1942 science fiction writer Isaac Asimov created the Three Laws of Robotics. They were written into a short story called "Runaround". Their influence on technological development has been significant and long lasting. Now, legal academic and AI expert Frank Pasquale has expanded that list. Building on Asimov's legacy, Professor Pasquale's four new laws of robotics are designed to ensure that the future development of artificial intelligence is done in the interest of humanity.

Deployment of Machine Learning Models in Production, Deploy ML Model in with BERT, DistilBERT, FastText NLP Models in Production with Flask, uWSGI, and NGINX at AWS EC2 Created by Laxmi Kant KGP TalkiePreview this course Udemy GET COUPON CODE Complete End to End NLP Application How to work with BERT in Google Colab How to use BERT for Text Classification Deploy Production Ready ML Model Fine Tune and Deploy ML Model with Flask Deploy ML Model in Production at AWS Deploy ML Model at Ubuntu and Windows Server Optimize your NLP Code You will learn how to develop and deploy FastText model on AWS Learn Multi-Label and Multi-Class classification in NLP Are you ready to kickstart your Advanced NLP course? Are you ready to deploy your machine learning models in production at AWS? You will learn each and every steps on how to build and deploy your ML model on a robust and secure server at AWS. Prior knowledge of python and Data Science is assumed. If you are AN absolute beginner in Data Science, please do not take this course. This course is made for medium or advanced level of Data Scientist.

* NexTech is expanding its technology stack by launching a new AI division * The Company is establishing a transformative internship program with AI students at Northeastern University and others * The global AI market revenues are expected to surpass $300 billion in 2024, creating a new substantial market opportunity for NexTech VANCOUVER, British Columbia, Dec. 02, 2020 (GLOBE NEWSWIRE) -- NexTech AR Solutions (NexTech) (OTCQB: NEXCF) (CSE: NTAR) (FSE: N29), a leading provider of virtual and augmented reality (AR) experience technologies and services for virtual and hybrid eCommerce, education, conferences and events today announced the creation of its new Artificial Intelligence (AI) division. Through a dedicated initial team of three AI experts focused on enhancing NexTech’s AI capabilities, the company aims to gain a competitive edge and create new portfolio offerings to complement its AR; streamlining operations for clients while tapping into a market that is expected to surpass $300 billion in revenues by 2024.NexTech’s Mirjana Prpa, AR Product Manager, and the new head of the AI division, will drive efforts to identify, develop and deploy AI capabilities within the Company’s existing AR technology and virtual experience portfolio. She will lead a growing team that will include new AI experts and a substantial number of interns. The NexTech AI program plans to create automation within the AR content creation space in order to build a self-service AR platform that easily works for everyone, turning everyone into AR creators. The AI program will give back to students while also tapping into their untapped potential and insight by developing an internship program, starting with computer science students at the nearby Northeastern University in Vancouver.The internships offered by NexTech’s AI division will provide students with a unique hands-on learning experience that equips them with the tools they need to establish their careers in AI and AR. NexTech aims to create a mutually beneficial experience where students will be able to grow with the company by working on various AI-focused projects. In addition, NexTech is committed to creating long-term opportunities that will allow students to work closely with the NexTech team in real-world AI applications.NexTech is building this new AI division with the goal of becoming a leader in AR which it believes can only happen with the merging of these two potent technologies. The team will utilize AI within the content creation of the company’s AR solutions that allow users to not just experience AR but also to create their own experiences, through the support of AI for AR. The ultimate goal is to harness the power of AI to offer a self-serve AR solution for everyone.“I’m excited to lead NexTech’s AI division and work towards the goal of making AR accessible to everyone. By creating a program that connects academia with industry experts, we hope to create long term relationships with students by recognizing their talents and offering them opportunities to aid in their professional development,” says Mirjana Prpa, Product Manager for AR and Head of the AI Division. “The potential of AI in AR applications is limitless; we’re only just starting to scratch the surface with this newfound program. Through the work of professionals and students who are learning new applications and approaches for AI integration, coupled with our growing team at NexTech, we hope to create experiences unlike any other currently available that combine the mesmerizing potential of AR with the streamlined efficiency of AI.”Evan Gappelberg, CEO of NexTech says, “As one of the leaders in the Augmented Reality market, we are excited to continue our leadership and development with the introduction of our AI division as well as our internship program. NexTech’s growth and competitiveness within the market remains an important aspect of the company’s identity, especially as we work to extend our capabilities and services into the rapidly growing AR/AI markets.”To learn more about NexTech AR, please visit www.nextechar.com.About NexTech ARNexTech is one of the leaders in the rapidly growing Augmented Reality market estimated to grow from USD $10.7B in 2019 and projected to reach USD $72.7B by 2024 according to Markets & Markets Research; it is expected to grow at a CAGR of 46.6% from 2019 to 2024.The company is pursuing four verticals:InfernoAR: An advanced Augmented Reality and Video Learning Experience Platform for Events, is a SaaS video platform that integrates Interactive Video, Artificial Intelligence and Augmented Reality in one secure platform to allow enterprises the ability to create the world’s most engaging virtual event management and learning experiences. Automated closed captions and translations to over 64 languages. According to Grandview Research the global virtual events market in 2020 is $90B and expected to reach more than $400B by 2027, growing at a 23% CAGR. With NexTech’s InfernoAR platform having augmented reality, AI, end-to-end encryption and built in language translation for 64 languages, the company is well positioned to rapidly take market share as the growth accelerates globally.ARitize™ For eCommerce: The company launched its SaaS platform for webAR in eCommerce early in 2019. NexTech has a ​‘full funnel’ end-to-end eCommerce solution for the AR industry including its Aritize360 app for 3D product capture, 3D/AR ads, its ARitize white label app it’s ‘Try it On’ technology for online apparel, 3D and 360-degree product views, and ‘one click buy’.ARitize™ 3D/AR Advertising Platform: Launched in Q1 2020 the ad platform will be the industry's first end-to-end solution whereby the company will leverage its 3D asset creation into 3D/AR ads. In 2019, according to IDC, global advertising spend will be about $725 billion.ARitize™ Hollywood Studios: The studio is in development producing immersive content using 360 video, and augmented reality as the primary display platform.To learn more, please follow us on Twitter, YouTube, Instagram, LinkedIn, and Facebook, or visit our website: https://www.nextechar.com.On behalf of the Board of NexTech AR Solutions Corp. “Evan Gappelberg” CEO and DirectorFor further information regarding the internship program, please contact:Mirjana Prpa Head of AI Division mirjana.prpa@nextechar.comThe CSE has not reviewed and does not accept responsibility for the adequacy or accuracy of this release.Certain information contained herein may constitute “forward-looking information” under Canadian securities legislation. Generally, forward-looking information can be identified by the use of forward-looking terminology such as, “will be”, “looking forward” or variations of such words and phrases or statements that certain actions, events or results “will” occur. Forward-looking statements regarding the Company increasing investors awareness are based on the Company’s estimates and are subject to known and unknown risks, uncertainties and other factors that may cause the actual results, levels of activity, performance or achievements of NexTech to be materially different from those expressed or implied by such forward-looking statements or forward-looking information, including capital expenditures and other costs. There can be no assurance that such statements will prove to be accurate, as actual results and future events could differ materially from those anticipated in such statements. Accordingly, readers should not place undue reliance on forward-looking statements and forward-looking information. NexTech will not update any forward-looking statements or forward-looking information that are incorporated by reference herein, except as required by applicable securities laws.

In this section we will learn - What does Machine Learning mean. What are the meanings or different terms associated with machine learning? You will see some examples so that you understand what machine learning actually is. It also contains steps involved in building a machine learning model, not just linear models, any machine learning model.

I have always worked with data, since high school, a long time ago in a galaxy far far away. Specifically, my background is astrophysics, with a Ph.D. in the subject. I performed astronomical data analysis, modeling, and simulation for 25 years, while also working on data repositories for space science satellite missions at NASA. I became very interested in the scientific discovery opportunities of very large datasets in the late 1990's, at which time I began my quest into machine learning, data mining, and data science. The motivation for me has always been discovery, from my early days until now.

MachineHack has successfully concluded The Great Indian Hiring Hackathon on 23rd of November 2020, where it collaborated for the first time with 12 companies to help data science professionals land up in a rewarding career. In this hackathon, the MachineHack community was asked to come up with an algorithm to predict the price of retail items belonging to different categories. In participation with companies like -- Aditya Birla Group, Bridgei2i, Concentrix, Fractal, Genpact, Lowe's, MiQ, Piramal, Scienaptic, Vmware, WellsFargo, and Zycus, the hackathon has witnessed an active attendance of whooping 5655 practitioners. Foretelling the retail price can be a daunting task due to the huge datasets with a variety of attributes ranging from text, numbers (floats, integers), as well as date and time. Also, outliers can be a big problem when dealing with unit prices. Thus this hackathon asked the participants to come out with a solution to forecast retail prices of items of different categories.