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Hoda Abokhadra

Membro dal giorno 2021

Campionato Argento

9760 punti
Badge per Machine Learning Operations (MLOps): Getting Started Machine Learning Operations (MLOps): Getting Started Earned mag 15, 2023 EDT
Badge per Recommendation Systems on Google Cloud Recommendation Systems on Google Cloud Earned mag 14, 2023 EDT
Badge per Production Machine Learning Systems Production Machine Learning Systems Earned mag 12, 2023 EDT
Badge per Machine Learning in the Enterprise Machine Learning in the Enterprise Earned mag 12, 2023 EDT
Badge per Feature Engineering Feature Engineering Earned mag 12, 2023 EDT
Badge per Natural Language Processing on Google Cloud Natural Language Processing on Google Cloud Earned mag 9, 2023 EDT
Badge per TensorFlow on Google Cloud TensorFlow on Google Cloud Earned mag 9, 2023 EDT
Badge per How Google Does Machine Learning How Google Does Machine Learning Earned apr 17, 2023 EDT
Badge per Launching into Machine Learning Launching into Machine Learning Earned apr 16, 2023 EDT
Badge per Scaling with Google Cloud Operations Scaling with Google Cloud Operations Earned nov 17, 2021 EST
Badge per Modernize Infrastructure and Applications with Google Cloud Modernize Infrastructure and Applications with Google Cloud Earned nov 17, 2021 EST
Badge per Exploring Data Transformation with Google Cloud Exploring Data Transformation with Google Cloud Earned nov 17, 2021 EST
Badge per Digital Transformation with Google Cloud Digital Transformation with Google Cloud Earned nov 17, 2021 EST
Badge per Networking Fundamentals in Google Cloud Networking Fundamentals in Google Cloud Earned nov 12, 2021 EST
Badge per Build a Secure Google Cloud Network Build a Secure Google Cloud Network Earned nov 12, 2021 EST
Badge per Language, Speech, Text, & Translation with Google Cloud APIs Language, Speech, Text, & Translation with Google Cloud APIs Earned nov 10, 2021 EST
Badge per Google Cloud Big Data and Machine Learning Fundamentals - Italiano Google Cloud Big Data and Machine Learning Fundamentals - Italiano Earned nov 10, 2021 EST
Badge per Cloud SQL Cloud SQL Earned nov 8, 2021 EST
Badge per Develop your Google Cloud Network Develop your Google Cloud Network Earned nov 5, 2021 EDT
Badge per Insights from Data with BigQuery Insights from Data with BigQuery Earned nov 4, 2021 EDT
Badge per BigQuery Basics for Data Analysts BigQuery Basics for Data Analysts Earned nov 4, 2021 EDT
Badge per Baseline: Deploy & Develop Baseline: Deploy & Develop Earned nov 3, 2021 EDT
Badge per Perform Foundational Infrastructure Tasks in Google Cloud Perform Foundational Infrastructure Tasks in Google Cloud Earned nov 1, 2021 EDT
Badge per Google Cloud Computing Foundations: Networking & Security in Google Cloud Google Cloud Computing Foundations: Networking & Security in Google Cloud Earned nov 1, 2021 EDT
Badge per Intro to ML: Language Processing Intro to ML: Language Processing Earned ott 31, 2021 EDT
Badge per Perform Foundational Data, ML, and AI Tasks in Google Cloud Perform Foundational Data, ML, and AI Tasks in Google Cloud Earned ott 30, 2021 EDT
Badge per Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud Earned ott 30, 2021 EDT
Badge per Baseline: Data, ML, AI Baseline: Data, ML, AI Earned ott 30, 2021 EDT
Badge per Kubernetes in Google Cloud Kubernetes in Google Cloud Earned ott 30, 2021 EDT
Badge per Cloud Engineering Cloud Engineering Earned ott 29, 2021 EDT
Badge per Baseline: Infrastructure Baseline: Infrastructure Earned ott 29, 2021 EDT
Badge per Implement Load Balancing on Compute Engine Implement Load Balancing on Compute Engine Earned ott 28, 2021 EDT
Badge per Google Cloud Computing Foundations: Cloud Computing Fundamentals Google Cloud Computing Foundations: Cloud Computing Fundamentals Earned ott 26, 2021 EDT
Badge per Google Cloud Essentials Google Cloud Essentials Earned ott 26, 2021 EDT
Badge per Google Cloud Computing Foundations: Infrastructure in Google Cloud Google Cloud Computing Foundations: Infrastructure in Google Cloud Earned ott 22, 2021 EDT

This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models.

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In this course, you apply your knowledge of classification models and embeddings to build a ML pipeline that functions as a recommendation engine. This is the fifth and final course of the Advanced Machine Learning on Google Cloud series.

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This course covers how to implement the various flavors of production ML systems— static, dynamic, and continuous training; static and dynamic inference; and batch and online processing. You delve into TensorFlow abstraction levels, the various options for doing distributed training, and how to write distributed training models with custom estimators. This is the second course of the Advanced Machine Learning on Google Cloud series. After completing this course, enroll in the Image Understanding with TensorFlow on Google Cloud course.

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This course takes a real-world approach to the ML Workflow through a case study. An ML team faces several ML business requirements and use cases. The team must understand the tools required for data management and governance and consider the best approach for data preprocessing. The team is presented with three options to build ML models for two use cases. The course explains why they would use AutoML, BigQuery ML, or custom training to achieve their objectives.

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This course explores the benefits of using Vertex AI Feature Store, how to improve the accuracy of ML models, and how to find which data columns make the most useful features. This course also includes content and labs on feature engineering using BigQuery ML, Keras, and TensorFlow.

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This course introduces the products and solutions to solve NLP problems on Google Cloud. Additionally, it explores the processes, techniques, and tools to develop an NLP project with neural networks by using Vertex AI and TensorFlow.

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This course covers designing and building a TensorFlow input data pipeline, building ML models with TensorFlow and Keras, improving the accuracy of ML models, writing ML models for scaled use, and writing specialized ML models.

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This course explores what ML is and what problems it can solve. The course also discusses best practices for implementing machine learning. You’re introduced to Vertex AI, a unified platform to quickly build, train, and deploy AutoML machine learning models. The course discusses the five phases of converting a candidate use case to be driven by machine learning, and why it’s important to not skip them. The course ends with recognizing the biases that ML can amplify and how to recognize them.

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The course begins with a discussion about data: how to improve data quality and perform exploratory data analysis. We describe Vertex AI AutoML and how to build, train, and deploy an ML model without writing a single line of code. You will understand the benefits of Big Query ML. We then discuss how to optimize a machine learning (ML) model and how generalization and sampling can help assess the quality of ML models for custom training.

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Organizations of all sizes are embracing the power and flexibility of the cloud to transform how they operate. However, managing and scaling cloud resources effectively can be a complex task. Scaling with Google Cloud Operations explores the fundamental concepts of modern operations, reliability, and resilience in the cloud, and how Google Cloud can help support these efforts. Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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Many traditional enterprises use legacy systems and applications that can't stay up-to-date with modern customer expectations. Business leaders often have to choose between maintaining their aging IT systems or investing in new products and services. 'Modernize Infrastructure and Applications with Google Cloud' explores these challenges and offers solutions to overcome them by using cloud technology. Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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Cloud technology can bring great value to an organization, and combining the power of cloud technology with data has the potential to unlock even more value and create new customer experiences. “Exploring Data Transformation with Google Cloud” explores the value data can bring to an organization and ways Google Cloud can make data useful and accessible. Part of the Cloud Digital Leader learning path, this course aims to help individuals grow in their role and build the future of their business.

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There's much excitement about cloud technology and digital transformation, but often many unanswered questions. For example: What is cloud technology? What does digital transformation mean? How can cloud technology help your organization? Where do you even begin? If you've asked yourself any of these questions, you're in the right place. This course provides an overview of the types of opportunities and challenges that companies often encounter in their digital transformation journey. If you want to learn about cloud technology so you can excel in your role and help build the future of your business, then this introductory course on digital transformation is for you. This course is part of the Cloud Digital Leader learning path.

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Networking is a principle theme of cloud computing. It’s the underlying structure of Google Cloud, and it’s what connects all your resources and services to one another. This quest will cover essential Google Cloud networking services and will give you hands-on practice with specialized tools for developing mature networks. From learning the ins-and-outs of VPCs, to creating enterprise-grade load balancers, Networking Fundamentals in the Google Cloud will give you the practical experience needed so you can start building robust networks right away.

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Earn a skill badge by completing the Build and Secure Networks in Google Cloud course, where you will learn about multiple networking-related resources to build, scale, and secure your applications on Google Cloud. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete the skill badge, and final assessment challenge lab, to receive a digital badge that you can share with your network.

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In this quest you will use a collection of Google APIs that are all related to language, and speech. You will use the Speech-to-Text API to transcribe an audio file into a text file, the Cloud Translation API to translate from one language to another, the Cloud Translation API to detect what language is being used and translate to a different language, the Natural Language API to classify text and analyze sentiment, and create synthetic speech.

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Questo corso presenta i prodotti e i servizi per big data e di machine learning di Google Cloud che supportano il ciclo di vita dai dati all'IA. Esplora i processi, le sfide e i vantaggi della creazione di una pipeline di big data e di modelli di machine learning con Vertex AI su Google Cloud.

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Cloud SQL is a fully managed database service that stands out from its peers due to high performance, seamless integration, and impressive scalability. In this quest you will receive hands-on practice with the basics of Cloud SQL and quickly progress to advanced features, which you will apply to production frameworks and application environments. From creating instances and querying data with SQL, to building Deployment Manager scripts and connecting Cloud SQL instances with applications run on GKE containers, this quest will give you the knowledge and experience needed so you can start integrating this service right away.

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Earn a skill badge by completing the Develop your Google Cloud Network course, where you learn multiple ways to deploy and monitor applications including how to: explore IAM rols and add/remove project access, create VPC networks, deploy and monitor Compute Engine VMs, write SQL queries, deploy and monitor VMs in Compute Engine, and deploy applications using Kubernetes with multiple deployment approaches. A skill badge is an exclusivedigital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge, and the final assessment challenge lab, to receive a skill badge that you can share with your network.

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Vuoi migliorare l'analisi dei dati senza dover gestire hardware del database? Scopri le best practice per le query e per ottenere informazioni dal tuo data warehouse con questa serie interattiva di lab su BigQuery. BigQuery è il database di analisi NoOps e a basso costo completamente gestito di Google. Con BigQuery puoi interrogare terabyte e terabyte di dati senza dover gestire alcuna infrastruttura o aver bisogno di un amministratore del database. BigQuery utilizza SQL e sfrutta i vantaggi offerti dal modello di pagamento a consumo. BigQuery permette di concentrarsi sull'analisi dei dati per trovare informazioni valide. Completa questo Laboratorio, compreso il Challenge Lab finale, per ricevere un esclusivo badge digitale Google Cloud.

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Want to scale your data analysis efforts without managing database hardware? Learn the best practices for querying and getting insights from your data warehouse with this interactive series of BigQuery labs. BigQuery is Google's fully managed, NoOps, low cost analytics database. With BigQuery you can query terabytes and terabytes of data without having any infrastructure to manage or needing a database administrator. BigQuery uses SQL and can take advantage of the pay-as-you-go model. BigQuery allows you to focus on analyzing data to find meaningful insights.

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In this introductory-level quest, you will learn the fundamentals of developing and deploying applications on the Google Cloud Platform. You will get hands-on experience with the Google App Engine framework by launching applications written in languages like Python, Ruby, and Java (just to name a few). You will see first-hand how straightforward and powerful GCP application frameworks are, and how easily they integrate with GCP database, data-loss prevention, and security services.

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Se sei uno sviluppatore cloud alle prime armi e vuoi mettere in pratica le conoscenze acquisite con "Getting Started - Create and Manage Cloud Resources", questo Laboratorio fa al caso tuo. Acquisirai esperienza pratica con i lab che si concentrano su Cloud Storage e altri servizi applicativi principali, tra cui Stackdriver e Cloud Functions. Completando questo Laboratorio, svilupperai competenze importanti applicabili a qualsiasi iniziativa Google Cloud. Completa questo Laboratorio, compreso il Challenge Lab finale, per ricevere un esclusivo badge digitale Google Cloud. I video di un minuto ti guideranno attraverso i concetti chiave di questi lab..

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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills. The courses should be completed in the following order: 1. Google Cloud Computing Foundations: Cloud Computing Fundamentals 2. Google Cloud Computing Foundations: Infrastructure in Google Cloud 3. Google Cloud Computing Foundations: Networking and Security in Google Cloud 4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud This third course covers cloud automation and management tools and building secure networks.

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It’s no secret that machine learning is one of the fastest growing fields in tech, and the Google Cloud Platform has been instrumental in furthering its development. With a host of APIs, GCP has a tool for just about any machine learning job. In this introductory quest, you will get hands-on practice with machine learning as it applies to language processing by taking labs that will enable you to extract entities from text, and perform sentiment and syntactic analysis as well as use the Speech to Text API for transcription.

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Big data, machine learning e intelligenza artificiale sono i temi più attuali nel campo dell'elaborazione dati. Tuttavia, questi settori sono piuttosto specialistici ed è difficile trovare materiale introduttivo. Fortunatamente, Google Cloud fornisce servizi facili da usare in questi ambiti e il Laboratorio Qwiklabs di livello preliminare ti aiuta a muovere i primi passi con strumenti come Big Query, API Cloud Speech e AI Platform. Completa questo Laboratorio, compreso il Challenge Lab finale, per ricevere un esclusivo badge digitale Google Cloud. I video di un minuto ti guideranno attraverso i concetti chiave di ogni laboratorio.

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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills. The courses should be completed in the following order: 1. Google Cloud Computing Foundations: Cloud Computing Fundamentals 2. Google Cloud Computing Foundations: Infrastructure in Google Cloud 3. Google Cloud Computing Foundations: Networking and Security in Google Cloud 4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud This final course in the series reviews managed big data services, machine learning and its value, and how to demonstrate your skill set in Google Cloud further by earning Skill Badges.

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Big data, machine learning, and artificial intelligence are today’s hot computing topics, but these fields are quite specialized and introductory material is hard to come by. Fortunately, Google Cloud provides user-friendly services in these areas, and with this introductory-level quest, so you can take your first steps with tools like Big Query, Cloud Speech API, and AI Platform. Want extra help? 1-minute videos walk you through key concepts for each lab.

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Kubernetes is the most popular container orchestration system, and Google Kubernetes Engine was designed specifically to support managed Kubernetes deployments in Google Cloud. In this advanced-level quest, you will get hands-on practice configuring Docker images, containers, and deploying fully-fledged Kubernetes Engine applications. This quest will teach you the practical skills needed for integrating container orchestration into your own workflow. Looking for a hands-on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, finish the additional Challenge Lab at the end of the Deploy to Kubernetes in Google Cloud Quest to receive an exclusive Google Cloud digital badge.

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This fundamental-level quest is unique amongst the other quest offerings. The labs have been curated to give IT professionals hands-on practice with topics and services that appear in the Google Cloud Certified Associate Cloud Engineer Certification. From IAM, to networking, to Kubernetes engine deployment, this quest is composed of specific labs that will put your Google Cloud knowledge to the test. Be aware that while practice with these labs will increase your skills and abilities, we recommend that you also review the exam guide and other available preparation resources.

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If you are a novice cloud developer looking for hands-on practice beyond Google Cloud Essentials, this quest is for you. You will get practical experience through labs that dive into Cloud Storage and other key application services like Stackdriver and Cloud Functions. By taking this quest, you will develop valuable skills that are applicable to any Google Cloud initiative. 1-minute videos walk you through key concepts for these labs.

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Complete the introductory Implement Load Balancing on Compute Engine skill badge to demonstrate skills in the following: writing gcloud commands and using Cloud Shell, creating and deploying virtual machines in Compute Engine, and configuring network and HTTP load balancers. A skill badge is an exclusive digital badge issued by Google Cloud in recognition of your proficiency with Google Cloud products and services and tests your ability to apply your knowledge in an interactive hands-on environment. Complete this skill badge, and the final assessment challenge lab, to receive a skill badge that you can share with your network.

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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills. The courses should be completed in the following order: 1. Google Cloud Computing Foundations: Cloud Computing Fundamentals 2. Google Cloud Computing Foundations: Infrastructure in Google Cloud 3. Google Cloud Computing Foundations: Networking and Security in Google Cloud 4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud This first course provides an overview of cloud computing, ways to use Google Cloud, and different compute options.

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In this introductory-level Quest, you will get hands-on practice with the Google Cloud’s fundamental tools and services. Google Cloud Essentials is the recommended first Quest for the Google Cloud learner - you will come in with little or no prior cloud knowledge, and come out with practical experience that you can apply to your first Google Cloud project. From writing Cloud Shell commands and deploying your first virtual machine, to running applications on Kubernetes Engine or with load balancing, Google Cloud Essentials is a prime introduction to the platform’s basic features. 1-minute videos walk you through key concepts for each lab.

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The Google Cloud Computing Foundations courses are for individuals with little to no background or experience in cloud computing. They provide an overview of concepts central to cloud basics, big data, and machine learning, and where and how Google Cloud fits in. By the end of the series of courses, learners will be able to articulate these concepts and demonstrate some hands-on skills. The courses should be completed in the following order: 1. Google Cloud Computing Foundations: Cloud Computing Fundamentals 2. Google Cloud Computing Foundations: Infrastructure in Google Cloud 3. Google Cloud Computing Foundations: Networking and Security in Google Cloud 4. Google Cloud Computing Foundations: Data, ML, and AI in Google Cloud

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