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NLP - Natural Language Processing with Python

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NLP - Natural Language Processing with Python Learn to use Machine Learning, Spacy, NLTK, SciKit-Learn, Deep Learning, and more to conduct Natural Language Processing Bestseller What you'll learn Welcome to the best Natural Language Processing course on the internet! This course is designed to be your complete online resource for learning how to use Natural Language Processing with the Python programming language. In the course we will cover everything you need to learn in order to become a world class practitioner of NLP with Python. We'll start off with the basics, learning how to open and work with text and PDF files with Python, as well as learning how to use regular expressions to search for custom patterns inside of text files. Afterwards we will begin with the basics of Natural Language Processing, utilizing the Natural Language Toolkit library for Python, as well as the state of the art Spacy library for ultra fast tokenization, parsing, entity recognition, and lemmatization of text.


AI Remote Learning for Professionals

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The way we work has changed and it's continuing to change. People are working remotely while being part of their team irrespective of the location. With this change, traditional training methods being restrictive and costly have become less relevant. One of the challenges faced by teachers is to provide customized learning catering to the needs of every student. As different students have different requirements, even teaching one student is an arduous task as the teacher is challenged to find the right curriculum to meet their requirements.



Using Computer Programs and Search Problems for Teaching Theory of Computation

Communications of the ACM

The theory of computation is one of the crown jewels of the computer science curriculum. It stretches from the discovery of mathematical problems, such as the halting problem, that cannot be solved by computers, to the most celebrated open problem in computer science today: the P vs. NP question. Since the founding of our discipline by Church and Turing in the 1930s, the theory of computation has addressed some of the most fundamental questions about computers: What does it mean to compute the solution to a problem? Which problems can be solved by computers? Which problems can be solved efficiently, in theory and in practice?


Fran Allen

Communications of the ACM

Frances E. Allen, an American computer scientist, ACM Fellow, and the first female recipient of the ACM A.M. Turing Award (2006), passed away on Aug. 4, 2020--her 88th birthday--from complications of Alzheimer's disease. Allen was raised on a dairy farm in Peru, NY, without running water or electricity. She received a BS degree in mathematics from the New York State College for Teachers (now the State University of New York at Albany). Inspired by a beloved math teacher, and by the example of her mother, who had also been a grade-school teacher, Allen started teaching high school math. She needed a master's degree to be certified, so she enrolled in a mathematics master's program at the University of Michigan.


MIT undergraduates pursue research opportunities through the pandemic

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Even in ordinary times, scientific process is stressful, with its demand for open-ended exploration and persistence in the face of failure. But the pandemic has added to the strain. In this new world of physical isolation, there are fewer opportunities for spontaneity and connection, and fewer distractions and events to mark the passage of time. Days pass in a numbing blur of sameness. Working from home this summer, students participating in MIT's Undergraduate Research Opportunities Program (UROP) did their best to overcome these challenges.


Complete 2020 Data Science & Machine Learning Bootcamp

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Created by Philipp Muellauer Preview this Udemy Course - GET COUPON CODE Welcome to the Complete Data Science and Machine Learning Bootcamp, the only course you need to learn Python and get into data science. At over 40 hours, this Python course is without a doubt the most comprehensive data science and machine learning course available online. Even if you have zero programming experience, this course will take you from beginner to mastery. Here's why: The course is a taught by the lead instructor at the App Brewery, London's leading in-person programming bootcamp. In the course, you'll be learning the latest tools and technologies that are used by data scientists at Google, Amazon, or Netflix.


MobileBERT Paper Summary

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As the size of the NLP model increases into the hundreds of billions of parameters, so does the importance of being able to create more compact representations of these models. Knowledge distillation has successfully enabled this but is still considered an afterthought when designing the teacher models. This probably reduces the effectiveness of the distillation, leaving potential performance improvements for the student on the table. Further, the difficulties in fine-tuning small student models after the initial distillation, without degrading their performance, requires us to both pre-train and fine-tune the teachers on the tasks we want the student to be able to perform. Training a student model through knowledge distillation will, therefore, require more training compared to only training the teacher, which limits the benefits of a student model to inference-time.


Women Leaders in AI - 2020 - NASSCOM Community

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The excitement of using Artificial Intelligence has not dwindled from the time it has been unfolded. In KPMG study on “living in the AI world 2020: achievements and challenges of AI across 5 industries (retail, financial service, healthcare, transportation, and technology), revealed that 92% of respondents agreed that leveraging the spectrum of AI technologies will make their companies run more efficiently. Amidst the admiration towards AI, IBM created the Women Leaders in AI program in 2019. This was a way to acknowledge the women leading in AI and encourage females to lend a hand in the field of AI. Through this IBM, planned to make the efforts of the honourees more visible to the world. 2020 IBM women leaders were honoured for outstanding leadership in the AI space. Here is the list of women leaders in AI 2020 honorees:- Aarthi Fernandez Who is a Global head of Trade Operations and SEA Trade COO at Standard Chartered Bank? She is a C-suite executive with deep insight on how digitalization can positively disrupt US$17 trillion global trade. She is into deploying AI/Machine learning to make trade financing simple, faster, and better for corporate clients and mitigate compliance risk. Piera Valeria Cordaro She is a commercial Operations Innovation Manager, Wing Tre S.p.A., Italy. She is a speaker, advocating the use of AI in customer operations. Along with her team and with support by IBM Watson, implemented two chatbots, to improve customer experience. Both bots have made it possible to handle a million queries efficiently. Amala Duggirala Who is the enterprise Chief operation and Technology officer, Regions Bank, United States. To handle customers’ inquiries she deployed IBM Watson’s assistant- virtual banker persona, ”Reggie”. From the time of its implementation 4.3 million customer calls have been answered, with 22% of them being handled by AI. Mara Reiff Vice President, Strategy and Business Intelligence, Beli Canada, Canada. She used AI to improve operations, loyalty, and brand. She worked with IBM to install Watson studio Local using Red Hat open shift. This resulted in smarter, fast decision-making with improved customer experience leading to increased sales. Mara suggests everybody to “Make sure to stop and smell the roses. Take each opportunity to learn something new and embrace change”. Amy Shreve- McDonald She is lead Product Marketing Manager for Business Digital experience, AI&T, USA. EVA (Enterprise Virtual Agent) was launched in February 2019, to improve customer chat experience, it uses Watson assistant. This system has been able to handle 45% chats on its own, resulting in reduced costs and expanding 24/7 support. She also received AT&T’s 2019 Visionary Award for her work advocating EVA. Ryoko Miyashita Manager, customer service department, customer service section JACCS CO., LTD Japan. She launched a Watson-enabled operator onboarding tool, that resulted in reduced new operator training period by 30%. The tool has increase customer satisfaction. Her advice to the younger self is “It is important to believe in yourself, but it is equally or more important to believe in people around you. I would encourage myself to have many experiences and garner knowledge to objectively evaluate things, not blindly accept or exclude others’ opinions”. Carol Chen She is Vice President for Global Marketing, Global Commercial, Royal Dutch Shell, United Kingdom. Along with her team, Carol is partnering is planning for digital transformation with the creation of “Oren”- a Smart Minning Platform, by partnering with IBM. This platform will offer an innovative and creative experience for users in the sector to deliver connectivity and integration across the ecosystem. To use AI, she advice commencing with analyzing the business outcome that one wants and customer pain points that one can cater to. The next step would be to determine how to leverage AI and data to solve the problem. Rosa Martinez Cognitive Project Manager, CiaxaBank, Spain. For those who consider using AI, her advice to them is ‘first to understand the business case as it may take time more than expected. This phase can result in a non-AI project example a ‘software as usual’. But moving further with the project there can be more AI application for sure to work on’. Lee- Lim Sok Know Deputy Principal, Temasek Polytechnic, Singapore. Under the leadership of Sok Keow, The higher education institution in Singapore ‘Temasek Polytechnic’ launched the “Ask TP” chatbot in January 2018. The chatbot helped current as well as prospective students to get answers to the questions asked about Temasek and also gave personalized course advice. In the 1st two weeks of 2020, ‘Ask’ TP’ responded to more than4,351 questions. She suggests everybody “deeply appreciate ‘people’ as they are the most critical asset in an organization, and a leader must develop a team”. Itumeleng Monale Executive Head of Enterprise Information Management Personal and Business Banking, Standard Bank of South Africa, South Africa. By deploying many analytical tools in her organization, she can uplift the revenue of the company. Through models of analytics relationships, bankers are experiencing a 40% revenue uplift when comparing to their peers. She sees AI as a tool through which business delivery can be accelerated, value could be added to human capital and relationships can build further. With this AI era, Research has postulated that corporate giants still have less percentage of women in the technical department. Facebook’s diversity report suggests that there are 22 % of women in the technical department and 15 per cent of women work in the AI research group. Similarly, Google’s diversity report suggests that only 10% women are working on  “machine intelligence”. There is a need to encourage women participation as there are many more women around the world, stepping out of the pre-existed sheathe and going beyond the walls to shape the future. Opening up the AI platform for all will fetch us more talented beings which can help us celebrate the use of AI in different fields and different ways. Reference:- https://www.ibm.com/watson/women-leaders-in-ai/2020-list https://advisory.kpmg.us/content/dam/advisory/en/pdfs/2020/technology-living-in-an-ai-world.pdf   About the author:- Kirti Kumar is a budding HR professional currently pursuing PGDM in HR and Marketing at New Delhi Institue of Management. She looks forward to opportunities that can hone her skills. She is agile in her attitude with versatility in her action


What's the best way to prepare for machine learning math?

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This article is part of "AI education", a series of posts that review and explore educational content on data science and machine learning. How much math knowledge do you need for machine learning and deep learning? Some people say not much. Both are correct, depending on what you want to achieve. There are plenty of programming libraries, code snippets, and pretrained models that can get help you integrate machine learning into your applications without having a deep knowledge of the underlying math functions.