Machine Learning and Python For Marketing Automation | MKGO October 2019 | Ruth Everett

The document appears to be a series of slides by Tim Kadlec on various technical SEO topics. Some key points covered include: - The benefits of AMP for page speed due to reduced payload and third party requests. However, AMP pages initially render slower due to asynchronous loading of custom elements. - Caching and pre-rendering pages on a CDN improves AMP performance versus loading from the main domain. - Google contributes the vast majority of code to the AMP Project and many see it as a way for Google to influence web standards. - Progressive Web Apps (PWAs) are discussed as an alternative to native apps that can provide app-like experiences through the browser.

People generally react to machine learning in one of two ways: either with a combination of fascination and terror brought on by the possibilities that lie ahead, or with looks of utter confusion and slight embarrassment at not really knowing much about it. With the advent of RankBrain, not even higher-ups at Google can tell us exactly how some things rank above others, and the impact of machine learning on SEO is only going to increase from here. Fear not: Moz's own senior SEO scientist, Britney Muller, will talk you through what you need to know.

Is there a state of technical SEO? Or is it simply a function of what’s happening with tech in broader disciplines like data/analytics, digital marketing, and web development? Join this session to get Mike King’s take on the state, or rather, statelessness of technical SEO. He’ll share the things you need to know to build an authentic picture of your technical SEO program and get on Google’s level.

One of the challenges faced at enterprise SEO level is often the legacy platforms and tech stacks that you inherit. Finding a cost-effective way of implementing international SEO best practice is often a barrier to internationalisation. Edge technology is creating new opportunities to optimise websites independently of the inherited technological barriers. In this session, SALT.agency’s Dan Taylor will explore their findings from implementing Hreflang using cutting edge technology to remove these barriers.

Are you tapping into automation for keyword research? If not, why not? When it comes to SEO, automation is awesome. For starters, it can help free up a lot of time that is normally spent on menial tasks. What’s more, it can also aid deep analysis, and even facilitate innovation. If you are still doing keyword research manually, this is a must-attend session. Paul will show you how to get started with automated keyword research, using some easy-to-use tools. You’ll see first-hand how they can help you uncover valuable insights automatically. Overall, you will walk away with an immediately actionable plan to start automating your keyword research today.

This document discusses various techniques for measuring and improving website performance. It provides links to tools for monitoring page speed metrics and the loading performance of different sites. Specific techniques are recommended for optimizing assets like JavaScript, CSS, images and HTTP requests to enhance performance. New technologies like HTTP/2 that can help and methods for testing performance variations are also referenced.

This document discusses how machine learning is shaping Google and technical SEO. It addresses how TF-IDF is not the best algorithm and that BM25 and machine learning take other factors into account. Wikimedia Research has released machine learning ranking models on GitHub. The document also discusses how Google may use click-through rate as a ranking factor alongside other signals processed by machine learning algorithms, and how techniques like query disambiguation, semantic relevance analysis, content deduplication, and evaluating click satisfaction should be focuses for technical SEO.

Google is constantly evolving and a webmaster’s ability to react to changes is key to any successful SEO campaign. However, what happens when you can’t get technical SEO recommendations over the line? This slideshow focuses on how you can be more Agile and implement technical SEO recommendations that add value.

Vincent Terrasi discusses using AI models like GPT-2 and BERT to generate qualitative content in different languages. He outlines the steps to fine-tune a GPT-2 model for a new language using SentencePiece to compress the training data into byte-pair encodings. With sufficient training data in that language, the model can generate fluent multi-sentence texts that pass quality checks by a native speaker and language analysis tool. However, limited training data results in weaker performance. Terrasi provides resources to experiment with a French GPT-2 model and encourages adapting the approach for other languages.

This document provides an overview of an event being held by Adaptavist in various cities in North America to demonstrate their ScriptRunner product. The agenda includes introductory presentations on ScriptRunner and how it can be used for support delivery and within Confluence, JIRA, and Bitbucket. There will also be a session demonstrating how to extend the user interface in JIRA. Participants can sign up to receive the presentation slides. The evening agenda includes a further overview of ScriptRunner and its new editor, followed by a question and answer session.

The document discusses a presentation about the journey to becoming a software testing master chef. It provides an overview of IBM Cloud Paks for Integration and Data, including the components included. It then discusses a use case of using these products to analyze customer spending history and behaviors. It outlines the testing methodology and challenges encountered with the products, and how they were resolved to delight stakeholders. Finally, it discusses best practices for testing and collaboration to improve quality.

Slide deck from April 27 2017 Atlassian User Group NYC session with speakers from Adaptavist: Riz Hassan Jamie Echlin Harp Athwal Mark McCormack

Historically, SEO was a very technical discipline. Over time, that shifted as Strategists began touting the death of SEO and claiming all you need is great content. Today, SEO is going back to those technical roots. From simple data markup to more complex proprietary technologies like AMP; now more than ever SEOs & marketers have to be technical masters. Learn why it's important to embrace these technical roots, what technologies we should be learning now, and how to stay ahead of the curve.

On this presentation we go deep on Chrome developer tools, JS debugger and breakpoints, technical optimization and capabilities of browser service workers to improve SEO and performance

Despite the huge shift to content marketing in recent years, the technical end of SEO has gotten increasingly complex and our tools are not keeping pace. As SEOs, we must develop strong working knowledge of the optimal usage of technology to get implementations accomplished. In this talk, Mike will walk through case studies, the impact of different technical implementations, and how to pull together small solutions when nothing on the shelf works for your needs.

This document discusses various rendering strategies and their impact on Core Web Vitals metrics. It begins by defining the Core Web Vitals metrics - Largest Contentful Paint, First Input Delay, and Cumulative Layout Shift. It then examines different rendering strategies like client-side rendering, server-side rendering, static rendering, and rehydration. For each strategy, it outlines potential issues that could lead to poor Core Web Vitals and provides mitigation tactics to address those issues. The goal is to help understand how rendering strategies affect page speed and provide ways to optimize for Core Web Vitals.

A discussion of trends in the technical SEO industry covering a wide array of topics from industry health metrics, budding technologies, standards adoption and future expectations.

Building a conversational AI experience that can respond to a wide variety of inputs and situations depends on gathering high-quality, relevant training data. Dialog with humans is an important part of this training process. In this session, learn how researchers at Facebook use Amazon Mechanical Turk within the ParlAI (pronounced “parlay”) framework for training and evaluating AI models to perform data collection, human training, and human evaluation. Learn how you can use this interface to gather high-quality training data to build next-generation chatbots and conversational agents.

This document provides an overview of artificial intelligence trends and applications in development and operations. It discusses how AI is being used for rapid prototyping, intelligent programming assistants, automatic error handling and code refactoring, and strategic decision making. Examples are given of AI tools from Microsoft, Facebook, and Codota. The document also discusses challenges like interpretability of neural networks and outlines a vision of "Software 2.0" where programs are generated automatically to satisfy goals. It emphasizes that AI will transform software development over the next 10 years.

The document provides information and instructions for accessing APIs from various organizations to use for a hackathon, including the Guardian API, Semantria API, DataSift API, and Amazon datasets. It includes tips for initial queries to make using the Guardian API, how to sign up and activate licenses for the DataSift API, and potential ideas for projects using clean energy and Olympic drug use data.

From data ingestion, processing, model deployment to prediction - machine learning is hard! Join me to learn how serverless can make it all easier so you can stop worrying about the underlying infrastructure layer, and focus on getting the most value out of your data and development time.

In the dynamic field of DevOps, the quest for efficiency and productivity is endless. This talk introduces a revolutionary toolkit: Large Language Models (LLMs), including ChatGPT, Gemini, and Claude, extending far beyond traditional coding assistance. We'll explore how LLMs can automate not just code generation, but also transform day-to-day operations such as crafting compelling cover letters for TPS reports, streamlining client communications, and architecting innovative DevOps solutions. Attendees will learn effective prompting strategies and examine real-life use cases, demonstrating LLMs' potential to redefine productivity in the DevOps landscape. Join us to discover how to harness the power of LLMs for a comprehensive productivity boost across your DevOps activities.

Apache Spark is one of the most popular Big Data frameworks today. It is fast becoming the de facto technology choice for stream processing, real-time analytics, data science and machine learning applications at scale. It has moved well beyond the early-adopter phase, is supported by a vibrant open source community and is enjoying accelerated adoption in enterprises. Join our guest speaker from Forrester Research, VP & Principal Analyst, Mike Gualtieri and StreamAnalytix, Product Head, Anand Venugopal for a discussion on the trends and directions defining the growing importance of Apache Spark for stream processing, machine learning and other advanced data analytics applications.

Building intelligent apps involves combining real-time analytics, machine learning, and artificial intelligence to provide personalized recommendations and automate tasks for customers. Developers can use MongoDB and Google Cloud to build intelligent apps in 3 steps: 1) create a base ecommerce app, 2) add a recommendation engine using machine learning, and 3) enable shopping via chat with artificial intelligence. This brings data scientists and developers together to create applications that understand and assist customers.

Introduction to Google Cloud data analysis and machine learning technologies, including DialogFlow and ML APIs.

This document discusses two experiments using large language models (LLMs) to make OpenSearch more accessible. The first experiment uses ChatGPT to automatically generate OpenSearch queries based on natural language questions by mapping data fields. The second experiment explores using Retrieval Augmented Generation to give LLMs access to vector databases for more contextual responses. Initial results showed ChatGPT was only able to generate the correct query 33% of the time. Further improvements are needed, such as fine-tuning models or providing more mapping information. The document also provides an overview of semantic search capabilities in OpenSearch using its neural search plugin.

Speaker: Seth Vargo Language: English Although not officially coined until 2009, DevOps ideals have been explicitly discussed since at least 2006. Recently, however, the term "DevOps" has gained increasing popularity across a variety of fields and industries. DevOps is not a development methodology or technology; DevOps is an ideology. It is a way to facilitate organizational prosperity and growth while increasing each individual employee's happiness along the way. As DevOps has gained in prominence, a gap has been created between the original definition of DevOps and this new "enterprise-ready" buzzword. For organizations beginning DevOps practices, this talk will provide a 10,000ft view of DevOps and how you can properly implement DevOps practices in your organization. For organizations that are currently practicing DevOps, this talk will cover common pitfalls, ways to sustain a happy culture, and new tips to foster organizational prosperity. Visit our website: http://atmosphere-conference.com/

This document discusses using retrieval augmented generation (RAG) with Cosmos DB and large language models (LLMs) to power question answering applications. RAG combines information retrieval over stored data with text generation from LLMs to provide customized, up-to-date responses without requiring expensive model retraining. The key components of RAG include data storage, embedding models to index data, a vector database to store embeddings, retrieval of relevant embeddings, and an LLM orchestrator to generate responses using retrieved information as context. Azure Cosmos DB is highlighted as an effective vector database option for RAG applications.

An overview of Artificial Intelligence and Machine Learning on AWS Join us to gain an understanding of a spectrum of easy-to-use AWS Machine Learning services such as Amazon Recognition, Amazon Polly and Amazon Comprehend that rely on AWS pre-built Machine Learning models. In addition, hear how Amazon SageMaker allows Machine Learning practitioners to collaborate on building models using Jupyter notebooks. Craft custom Deep Learning algorithms using popular libraries such as TensorFlow, Keras, MXNet, or work with traditional Machine Learning algorithms such as XGBoost. You will also learn how to detect anomalies using Amazon Kinesis Analytics.

The presentation is showing what type of SEO techniques you can apply to optimize your Drupal site and all this only with contributed modules.

Presented at React Alicante 2022, Spain https://reactalicante.es/ Type systems like TypeScript are the next thing when developing JavaScript applications. They make sure that your props are passed in the correct form and shape throughout your application. Together with GraphQLs query language based on types, you can create the web application of the future!

Many organisations are creating groups dedicated to data. These groups have many names : Data Team, Data Labs, Analytics Teams…. But whatever the name, the success of those teams depends a lot on the quality of the data infrastructure and their ability to actually deploy data science applications in production. In that regards a new role of “DataOps” is emerging. Similar, to Dev Ops for (Web) Dev, the Data Ops is a merge between a data engineer and a platform administrator. Well versed in cluster administration and optimisation, a data ops would have also a perspective on the quality of data quality and the relevance of predictive models. Do you want to be a Data Ops ? We’ll discuss its role and challenges during this talk

This was presented by the Yongsheng Wu, head of big data and ML platform at Pinterest, at the Alluxio bay area meetup. Yongsheng shares Pinterest's journey to build a fast and scalable big data and ML platform in AWS for Pinterest to handle the requests and complexity in data at scale. In this talk, he will cover different aspects from the requirements of the platform, the challenges encountered, the technologies chosen, and the tradeoffs that were made.

People are complex. Office 365 is complex. Add the two together and you get some of the most challenging, difficult, and stressful situations, especially if you are responsible for facilitating shared understanding between them. Join Richard Harbridge to learn about actionable techniques to improve, simplify and amplify your leadership, business analysis and information architecture efforts with Office 365. Walk away with improved confidence when dealing with business and non-technical related challenges of Office 365, and be familiarized with effective tools and techniques that make Office 365 implementations more successful.

This document describes a Twitter analysis project performed in RStudio using R programming. The analysis included collecting tweets containing the hashtag "#Kejriwal", performing sentiment analysis to score the tweets as positive, negative or neutral, and visualizing the results. Text mining was also conducted on the tweets. The sentiment analysis found most tweets had a negative sentiment towards Kejriwal, while text mining showed the most common words in tweets were "Kejriwal", "power", "cut" and "Modi".

If you want to hire a python development company to outsource your project, first, you need to know what it takes to choose the best one out of many. While many articles talk about the list of companies, we talk about how to find the best fit. Read on to know the necessary information before you reach out to outsource any company!

Over the next few years, every company must develop a strategy to leverage artificial intelligence and machine learning to stay relevant and beat out competitors. This requires hiring talented data scientists as well as DevOps and data engineers who can put these into production. Today, finding that perfect combination of talent can be difficult, but a focus on retraining and productivity tools can increase a small team’s impact on business ROI by over 10x. In this technical talk, we discuss how enterprises can better prepare their employees to deploy artificial intelligence and machine learning into production by using the same techniques used in software to add provenance, reliability, and efficiency to these processes. Specifically, we describe the benefits of adding provenance including reliable deployments and builds, A/B testing, continuous deployment, and automation and show how they can decrease the time to business ROI by over 10x.

You'll learn about proven systems and effective workflows to maintain a consistent and engaging social media strategy. Additionally, you'll gain actionable strategies and practical tactics to drive engagement, increase followers, and convert them into loyal customers.

Mobile marketing presentation with ppt tag to easily editing and easy to use

A presentation for the Digital Marketing World Forum by Jessica Redman and Andrew Fox. Discussing how SEO supports across numerous marketing channels and how user search behaviour is changing. Discover how to optimise social media posts for discoverability and learn about Topical Domination.

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Struggling to get high-quality backlinks? Our latest presentation reveals the strategies you need to succeed in 2024. Learn practical tips to boost your SEO and elevate your website’s authority. Click below to access the full presentation! Full blog here - https://digitalmarketingphilippines.com/how-to-get-high-quality-backlinks-in-2024/