Assignment 1 final

Google Translate is a free online translation service that can translate text between 58 languages. It uses statistical machine translation by looking for patterns in large amounts of translated text to determine the best translation. While not perfect, translation accuracy varies by language and is better for shorter texts. The future may include voice translation and improved quality as more text is analyzed.

Google services

Google Translate is a free online translation service that can translate text between 58 languages. It uses statistical machine translation by looking for patterns in large amounts of translated text to determine the best translation. While not perfect, translation accuracy varies by language and is better for shorter texts. In the future, voice translation may improve and translation quality is expected to get better as more text is analyzed.

Google services >>

Managing Your Machine Learning Portfolio

David Murgatroyd

Applying machine learning to a particular business need becomes more straightforward with each technological advance. But today’s businesses have a variety of needs which are too numerous to be addressed one-at-a-time and too different to be addressed one-size-fits-all. We examine three significant challenges to building an effective ML portfolio and ways to address them thru the framework of the ML product lifecycle.

Natural Language Processing (NLP), Search and Wearable Technology

pixelbuilders

Google Translate is a free online translation service that can translate text between 58 languages. It uses statistical machine translation by looking for patterns in large amounts of translated text to determine the best translation. While not perfect, translation accuracy varies by language and is better for shorter texts. In the future, voice translation may improve and translation quality is expected to get better as more text is analyzed.

Google services >>

Managing Your Machine Learning Portfolio

David Murgatroyd

Natural Language Processing (NLP), Search and Wearable Technology

pixelbuilders

New trends in NLP applications

Constantin Orasan

Tutorial given at RANLP 2015 in Hissar, Bulgaria Recent years have seen lots of changes in the field of computational linguistics, most of them due to the widespread use of the Internet and the benefits and problems it brings. The first part of this tutorial will discuss these changes and will focus on crowdsourcing and how it influenced the creation of annotated data. Annotation of data employed to train and test NLP methods used to be the task of language experts who had a good understanding of the linguistic phenomena to be tackled. Given that a large number of people now have access to the Internet, crowdsourcing has become an alternative way of obtaining annotated data. The core idea of crowdsourcing is that it is possible to design tasks that can be completed by non-experts and that the outputs of these tasks can be combined to obtain high-quality linguistic annotation, which would normally be produced by experts. Examples of how crowdsourcing was employed in computational linguistics will be given. Big data is another trend in computational linguistics as researchers rely on more and more data for improving the results of a method. The second part of the tutorial will introduce the MapReduce programming model and show how it was used in processing language. Combined with processing larger quantities of data, the field of computational linguistics has applied deep learning to various tasks successfully, improving their accuracy. An introduction to deep learning will be provided, followed by examples of how it was applied to tasks such as learning semantic representations, sentiment analysis and machine translation evaluation.

Extending the google_assistant

Ndjido Ardo BAR

This document provides an overview and agenda for building a natural language understanding model and rental application using the Google Assistant. It discusses building an NLU model with Dialogflow to understand user intents and entities, fulfilling requests with Actions on Google using Cloud Functions, and ways to interact with users through speech, text, cards and permissions. The goal is to build a hands-on rental shisha application that can be accessed through the Google Assistant.

Google services

tahamj1987

Google was founded in 1998 by Larry Page and Sergey Brin as a search engine called BackRub. It was later renamed Google, which is a reference to the mathematical term 'googol' meaning 1 followed by 100 zeros. Google Translate provides instant translations between 58 languages using statistical machine translation, which looks for patterns in large amounts of previously human-translated text. While it works well for general understanding, the accuracy can vary depending on language and length of text. Future predictions include voice translation and higher quality translations as more text is analyzed.

Resume - Alsey Coleman Miller

Alsey Miller

Seasoned iOS Developer experienced in designing and developing custom applications ranging from home automation, to social and business apps. Works well independently as a Freelancer and in teams of all sizes. Anticipates customer needs and meets project requirements. Skilled in cross-cultural communication. Natural learner. In the top 1% most active open source Swift contributors on GitHub (4000+ commits and 1500+ stars in 2016). Contributed to Swift compiler and reverse engineered Apple’s Foundation framework and UIKit. Also loves Hackintoshes.

Jeff Dean at AI Frontiers: Trends and Developments in Deep Learning Research

AI Frontiers

In this talk at AI Frontiers conference, Jeff Dean discusses recent trends and developments in deep learning research. Jeff touches on the significant progress that this research has produced in a number of areas, including computer vision, language understanding, translation, healthcare, and robotics. These advances are driven by both new algorithmic approaches to some of these problems, and by the ability to scale computation for training ever large models on larger datasets. Finally, one of the reasons for the rapid spread of the ideas and techniques of deep learning has been the availability of open source libraries such as TensorFlow. He gives an overview of why these software libraries have an important role in making the benefits of machine learning available throughout the world.

Tds — big science dec 2021

Gérard Dupont

BigScience is a one-year research workshop involving over 800 researchers from 60 countries to build and study very large multilingual language models and datasets. It was granted 5 million GPU hours on the Jean Zay supercomputer in France. The workshop aims to advance AI/NLP research by creating shared models and data as well as tools for researchers. Several working groups are studying issues like bias, scaling, and engineering challenges of training such large models. The first model, T0, showed strong zero-shot performance. Upcoming work includes further model training and papers.

Natural Language Processing in Artificial Intelligence - Codeup #5 - PayU

Artivatic.ai

Icwl2015 wahl

Presentation 4 1 REDY ok.pptx

SambitkumarBarik2

ChatGPT is a powerful language model developed by OpenAI to understand and generate natural language in various contexts like conversation. It works by analyzing patterns in large amounts of language data to understand context and respond relevantly. While ChatGPT has many applications and advantages like diversity and scalability, limitations include potential bias, lack of common sense, and inability to reason complexly. Overall, ChatGPT demonstrates significant progress in natural language processing.

Text-mining and Automation

benosteen

God Mode for designing scenario-driven skills for DeepPavlov Dream

Daniel Kornev

The document summarizes the capabilities and development of DeepPavlov, an open-source conversational AI platform. It discusses DeepPavlov's God Mode for building open-domain bots using a discourse-driven integrated dialog development environment. DeepPavlov utilizes speech functions and dialog acts to enable more predictable dialog design and improves over regular expressions and intents. The platform provides tools like a VSCode extension to help with rapid dialog design and skills development.

leewayhertz.com-How to build a GPT model (1).pdf

KristiLBurns

GPT models are a collection of deep learning-based language models created by the OpenAI team. Without supervision, these models can perform various NLP tasks like question-answering, textual entailment, text summarization, etc. These language models require very few or no examples to understand tasks. They perform equivalent to or even better than state-of-the-art models trained in a supervised fashion.

EdMedia2013 - Educational Impacts of the Intelligent Integrated Computer-Assi...

Kristine Schachinger SEO and Online Marketing

The document discusses the Intelligent Integrated Computer-Assisted Language Learning (iiCALL) environment. It aims to improve language skills for specific contexts through an integrated e-learning system using resources from language corpora enriched with semantic information. The system architecture includes various platforms and uses natural language processing, a dynamic data model, and software framework. Research-based learning activities are designed to build knowledge and competencies in areas like requirements engineering, software design, and project management. Learning outcomes include knowledge of e-learning standards and skills like documentation and teamwork.

Brighton SEO 2021 | The Mother of all Updates - What Google's MUM update will...

Oban International

With the recent announcement of their MUM algorithm update, Google has thrown the world of SEO into a state of flux. With their focus on delivering the most relevant search results to users, irrespective of market or language, international marketers will need to update their strategies and multilingual websites will need to respond to compete effectively in a ‘language agnostic’ future. We take you through how, for those suitably prepared, this can be a massive opportunity not just for global brands but also for those looking to go international for the first time.

Nautral Langauge Processing - Basics / Non Technical

Dhruv Gohil

This document provides an overview of natural language processing (NLP) and discusses several NLP applications. It introduces NLP and how it helps computers understand human language through examples like Apple's Siri and Google Now. It then summarizes popular NLP toolkits and describes applications including text summarization, information extraction, sentiment analysis, and dialog systems. The document concludes by discussing NLP system development, testing, and evaluation.

24 Ways to Shut Down The Application and Other Apocryphal Stories

Scott Abel

This document discusses challenges with global content management and localization. It provides examples of product names and slogans that were poorly translated, such as "Pepsi Brings Your Ancestors Back from the Grave." The document advocates for centralized authoring tools and resources to promote consistent terminology and styles across languages in order to improve translation quality and avoid issues that can damage brands.

Usability Study: Auralog Language Learning Library Solutions

Gwen Williams

The document provides a review of Auralog's language learning software after a 30 day trial. It summarizes that: 1) The software is only compatible with Windows XP/Vista operating systems, limiting many Mac and Linux users. 2) The content seeks to teach language fundamentals and fluency through lessons organized around everyday situations, but explanations of grammar are hidden requiring users to discover them. 3) While the navigation and routines are clear once learned, many features are hidden and it takes too many clicks to access activities, making the software difficult to use.

Watch your language, young man!

Paweł Wacławczyk

The document discusses the importance of language in software development. It explains that the language we use to describe problems, requirements, and code can impact how well we understand the domain and communicate with stakeholders. It recommends techniques like impact mapping, event storming, ubiquitous language, behavior-driven development, and pattern languages to help ensure the language we use supports the goals of the business and allows for effective collaboration.

Help Content Strategy presentation, iDW Oct 2014

Chris Todd

Google Machine Learning Algorithms and SEO

Untitled presentation (3)

This document appears to be a student assignment submitted by Issybella Lang for their course 102b under Professor Klinkowstein. It discusses the development of a concept for a vending machine that provides customized sunglasses. The assignments include research on the topic, creating personas and customer journey maps, developing the brand name and logo, designing social media pages and posts to promote the concept, and prototyping a website.

Untitled presentation (2)

This document appears to be a student assignment submitted by Issybella Lang for their FA 102b class. It includes research and work on developing a concept for a vending machine that provides customized sunglasses. The concept involves kiosks that use scanning technology to recommend the best fitting sunglasses to users based on their preferences and face shape. The document outlines persona descriptions, user experience maps, naming, logo design, social media planning and other elements of developing the product idea.

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New trends in NLP applications

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tahamj1987

Resume - Alsey Coleman Miller

Alsey Miller

Jeff Dean at AI Frontiers: Trends and Developments in Deep Learning Research

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Tds — big science dec 2021

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Watch your language, young man!

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Assignment 6

Untitled presentation

This document appears to be a student assignment submitted by Issybella Lang for their course 102b under Professor Klinkowstein. It discusses the development of a concept for a real-time custom sunglass vending machine that can recommend the best fit for an individual. The assignment includes persona descriptions, user experience maps, naming the concept "Customvated", designing a logotype, and creating a mission statement for a Facebook page describing the concept.

102b

102b powerpoint

The document discusses a student assignment to research an automated sunglasses vending machine that uses technology to recommend the best fit. It outlines the student's research process, including a description of their persona as a busy and stylish sunglasses wearer aged 15 or older. It also maps the user experience, describing how potential customers might encounter the product online through influencers, ads and the company website, and offline in locations like beaches, malls and campuses. The vending machine is meant to provide personalized sunglasses recommendations and a readily available, easy purchasing process to replace traditional manufacturing.

102b powerpoint