“…The third volume on measurement is the most applied and practical one because it discusses all the measures used, and presents new measures. Even for those who do not want to study well-being per se, but want to use some well-being measures in their research, this volume will be of enormous help. …”

“…The third volume on measurement is the most applied and practical one because it discusses all the measures used, and presents new measures. Even for those who do not want to study well-being per se, but want to use some well-being measures in their research, this volume will be of enormous help. …”

“…In conclusion, this book questions the naturalization of national canons by uncovering the gender politics behind what is cast as naturally determined by language and geography. Doing this also exposes the parallel gender strictures at work behind seemingly opposed central (Spanish) and peripheral (Galician) national projects…”

“…The paper demonstrates the ways in which participation of women has declined and ultimately leaves the readers with the question of what the community can do to improve the situation. The paper has been cited over 650 times and has had a profound influence on many notable works discussing gender disparities in undergraduate computing since its initial publication. …”

“…Conclusions Due to spare and low quality documentation, we do not know if HPV RNA tests have a better diagnostic accuracy compared to HPV DNA tests and cytology for detection of cervical pre cancer lesions. …”

“…This course is divided in 4 weeks: Week 1 Working with Data in Python By the end of Week 1 you'll be able to: Apply Python data structures like lists, dicts Extract data from sources like CSV, JSON Load and persist data using JSON Lesson 1: Data Structures in Python Lesson Outline Lists, tuples, dictionaries Working with pandas DataFrames Loading data files like CSV into data structures Lesson 2: Reading and Writing Data Lesson Outline Reading and writing CSV files Serializing Python objects with JSON Parsing and dumping JSON data Lesson 3: Persisting and Loading Data in Python Lesson Outline Loading data from files Saving data from Python to disk Loading and saving data to JSON Week 2 Python Scripting and SQL By the end of Week 2 you'll be able to: Write reusable Python scripts Use SQLite to persist data Query SQLite databases with Python Lesson 1: Python Scripting Techniques Lesson Outline Writing modular, reusable Python scripts Exception handling and logging Python virtual environments Lesson 2: Python with SQLite Lesson Outline Creating SQLite databases from Python Writing tables with SQLAlchemy Querying SQLite from Python with SQLAlchemy Week 3 Learning Objectives By the end of Week 3 you'll be able to: Scrape and collect data from websites Build scalable scraping scripts Persist scraped data to files/databases Lesson 1: Web Scraping with Python Lesson Outline HTML parsing and structure Using Beautiful Soup for scraping Storing scraped data in Python Lesson 2: Scalable Web Scraping Lesson Outline Scraping best practices Scaling scraping with multiprocessing Storing scraped data in databases Week 4 Learning Objectives By the end of Week 4 you'll be able to: Connect to MySQL from Python Execute SQL statements and queries Import and export data from MySQL Lesson 1: Python and MySQL Lesson Outline Installing MySQL and configuration Connecting Python to MySQL Executing queries and statements Lesson 2: Running SQL queries from VSCode Use Visual Studio Code to build SQL queries Execute and review SQL queries from Visual Studio Code Lesson 3: Importing and Exporting Data Lesson Outline Loading and exporting CSV data Best practices for moving data into MySQL Automating data imports with Python About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. …”

“…Domain 1: Data Engineering 1.0 course intro 1.1 technology prerequisite 1.2 sagemaker studio lab 1.3 learn aws cloudshell 1.4 cloud developer workspace advantage 1.5 prototyping ai apis aws cloudshell bash 1.6 cloud9 with codewhisperer 1.7 domain one intro 1.8 data storage 1.9 determine storage medium 1.10 using s3 demo 1.11 job styles batch vs streaming 1.12 data ingestion pipelines 1.13 aws batch demo 1.14 step function demo Domain 2: Exploratory Data Analysis 2.0 domain intro Sanitize and prepare data for modeling 2.1 cleanup data 2.2 scaling data 2.3 labeling data 2.4 mechanical turk labeling Perform feature engineering 2.5 identify extract features 2.6 feature engineering concepts Analyze and visualize data for machine learning 2.7 graphing data 2.9 clustering Conclusion 2.10 conclusion Domain 3: Modeling 3.0 domain intro Frame business problems as machine learning problems 3.1 when to use ml 3.2 supervised vs unsupervized 3.3 selection right ml solution Select the appropriate model(s) for a given machine learning problem 3.4 select models 3.5 sagemaker canvas demo Train machine learning models 3.6 train test split 3.7 optimization 3.8 compute choice Perform hyperparameter optimization 3.14 neural network architecture Evaluate machine learning models 3.18 overfitting vs underfitting 3.19 selecting metrics 3.22 compare models experiment tracking Conclusion 3.23 Conclusion Domain 4: Machine Learning Implementation and Operations 4.0 course intro Build machine learning solutions for performance, availability, scalability, resiliency, and fault 4.1 logging monitoring 4.2 multiple regions 4.3 reproducible workflow 4.4 aws flavored devops Recommend and implement the appropriate machine learning services and features for a given 4.5 provisioning ec2 4.5 compute choices 4.6 provisioning ebs 4.7 aws ai ml services Apply basic AWS security practices to machine learning solutions. 4.9 plp aws lambda 4.10 integrated security Deploy and operationalize machine learning solutions 4.13 sagemaker workflow 4.14 doing predictions with sagemaker canvas 4.16 retrain models Conclusion 5.0 course conclusion Topics Covered Include: Domain 1: Data Engineering Domain 2: Exploratory Data Analysis Domain 3: Modeling Domain 4: Machine Learning Implementation and Operations Additional Popular Resources Pytest Master Class AWS Solutions Architect Professional Course Github Actions and GitOps in One Hour Video Course Jenkins CI/CD and Github in One Hour Video Course AWS Certified Cloud Practitioner Video Course Advanced Testing with Pytest Video Course AWS Solutions Architect Certification In ONE HOUR Python for DevOps Master Class 2022: CI/CD, Github Actions, Containers, and Microservices MLOPs Foundations: Chapter 2 Walkthrough of Practical MLOps Learn Docker containers in One Hour Video Course Introduction to MLOps Walkthrough AZ 900 (Azure Fundamentals) Quick reference guide 52 Weeks of AWS Episode 8: Infrastructure as Code with CDK and AWS Lambda Learn GCP Cloud Functions in One Hour Video Course Python Devops in TWO HOURS! …”

Tabla de Contenidos: “…Sonetto 22 (h . 112 r.) . vv.: De dó, sobrino Iuan, con pedorreras?.. . (h . 112 r.) . 23 . …”

“…School of Law, Makerere University, Uganda Table of Contents Foreword Preface Acknowledgments About the author Dedication Cases, statutes and documents Acronyms Conceptualising the role of NGOs in the human rights movement 1 Introduction and overview 2 The concealed and unchecked power of NGOs: A background discussion 3 Linking rights, governance and development 4 Book overview The human rights obligations of NGOs in the international arena 1 Introduction 2 NGOs’ obligations under international law 2.1 NGOs do not have legal obligations under international human rights law 2.2 NGOs legal obligations to respect and promote human rights 3 The rights-based approach as an instrument of good governance 4 Implications of the rights-based approach to NGO governance 4.1 Express linkage to human rights 4.2 Accountability and Transparency 4.3 Participation and inclusion 4.4 Equity, non-discrimination and empowerment 5 Conclusion NGOs and the principle of express linkage to human rights 1 Introduction 2 Why all NGOs should apply human right principles to their governance and management 3 The principle of express linkage to rights and the universality of human rights 3.1 The universality of rights: The conceptualisation of rights amongst NNGOs and SNGOs 3.2 The universality of rights: African NGOs and cultural interpretation 4 The principle of indivisibility of rights: A case study of DNGOS and HURINGOs 4.1 The traditional relationship between DNGOs and HURINGOs 4.2 The indivisibility of rights: HURINGOs and the development agenda 5 Conclusion NGOs and the principle of accountability 1 Introduction 2 Accountability through the law 2.1 The right to exist informally as an organisation 2.2 The right to legal existence and the obligation to register 2.3 Protection from unwarranted state interference 3 Accountability to the sector wide mechanism for self-regulation 4 Accountability to the NGO Board 4.1 The Board as a source of accountability 4.2 The mechanisms of accountability by the Board 4 Accountability to members 5 Accountability to the communities 6 Transparency and public accountability 7 Accountability to donors 8 Conclusion NGOs and the principles of participation and inclusion 1 Introduction 2 Founders and inclusive and participatory management 3 Broadening participation through transitions and succession 4 Participation and the management of conflicts 5 NGOs and community participation 6 Peer NGO networks and coalitions 7 Participation of NGOs in political society 7.1 Making the case for NGO’s political participation 7.2 Collaboration and critical engagement with government 7.3 Civil disobedience 7.4 Entering the state 8 NGOs and the African Commission on Human and Peoples’ Rights 9 NGO participation with National Human Rights Institutions (NHRIs) 10 Conclusion Exploring the principles of empowerment, equity and non-discrimination 1 Introduction 2 NGOs, empowerment and human rights and governance expertise 2.1 NGOs and human rights and governance expertise 2.2 The dilemmas of volunteerism and the payment of competitive remuneration 2.3 Empowerment and sustaining activism 3 Empowerment and resource mobilisation to achieve an NGO’s mission 3.1 NGOs and government funding 3.2 NGOs and foreign donor funding 4 Empowerment of marginalised groups within the NGO sector 4.1 NGOs and the empowerment of women 4.2 NGOs and the empowerment of the youth 4.3 NGOs and sexual minorities 4.4 NGOs and the empowerment of racial and ethnic minorities 5 The contemporary efforts of promoting equality and empowerment within the NNGOs/ SNGO relationship 6 Conclusion Walking the talk: Holding NGOs accountable to human rights principles 1 Introduction 2 NGOs’ human rights obligations 3 NGOs’ human rights obligations elaborated 3.1 The principle of express linkage to rights (mainstreaming) 3.2 The principles of accountability and transparency 3.3 The principle of participation and inclusion 3.4 The principles of equity, non-discrimination and empowerment 4 Status of NGOs’ observance of human rights obligations in Kenya, Tanzania, Uganda and South Africa 4.1 The status of observance of the principle of linkage to rights 4.2 The status of observance of the principles of accountability and transparency 4.3 The status of observance of the principles of participation and inclusion 4.4 The status of observance of the principles of equity, non-discrimination and empowerment 5 Recommendations 5.1 NGO obligations under the principles of linkage to rights 5.2 NGO obligations under the principles of accountability and transparency 5.3 NGO obligations under the principles of participation and inclusion 5.4 Equity, Non-discrimination and Empowerment 6 Concluding thoughts Bibliography…”

“…At the end of the course, you will not only know what predictive analytics is and what it can do for an organization but also develop basic skills to practice predictive analytics using numerous tools and platforms, most of which are free and open source. …”

“…One of the questions we regularly get asked by readers is 'Where do we start with MDM?' In this book they will find not only the solution to creating buy-in and successfully launching an initiative, but more importantly, maturing MDM for the long-haul with sound data governance, data quality and change management techniques." …”

“…Those tasked with forecasting the cost and duration of an upcoming software development effort who want to do so with an Agile approach. Individuals tracking the progress of an Agile software development effort who need practical methods to set expectations with teams and stakeholders. …”

“…Search strategy and method The review team has performed a health technology assessment according to internationally appoved principles by doing a systematic review of the published literature. …”

“…Week 1: Setting up your development environment Reference GitHub Repository Setting up your text editor Using GitHub Copilot with Rust Introduction to GitHub Codespaces for Rust Week 2: Rust fundamentals Reference GitHub Repository Introduction to Rust Loops and Control flow Function basics Week 3: Structs, Types, and Enums Reference GitHub Repository Using structured data Exploring strings and vectors Working with Enum and Variants Week 4: Applying Rust Reference GitHub Repository Building a real-world library Extending functionality with modules Testing Rust code About your instructor Alfredo Deza has over a decade of experience as a Software Engineer doing DevOps, automation, and scalable system architecture. …”

“…The lesson also discusses building a high-performance GPU-accelerated Hugging Face Translator CLI using Rust. 2.0 High Performance MLOPs with Rust Hugging Face doing Zero Shot Classification 2.1 systems programming rust vs python for MLOPs 2.2 Building a high-performance data engineering tool with Rust that deduplicates data using Rayon with safe and memory efficient concurrency 2.3 Building a high-performance GPU-accelerated Hugging Face Translator CLI with Rust Lesson 3: Building GPU-accelerated MLOps with Rust In this lesson, we discuss the setup of reproducible GitHub Codespaces for GPU workflows using Stable Diffusion with Rust PyTorch bindings. …”

“…In Vietnam, I learned how to lead men under difficult and dangerous circumstances, and swore I never wanted to do it again. Law school and private practice followed, but I was bored. …”

“…: 2.40-what-is-colab.mp4 Using Bard to enhance notebook development: 2.41-using-bard-to-enhance-productivity.mp4 Exploring Life Expectency in a Notebook: 2.42-life-expectancy-eda.mp4 Load a DataFrame with sensitive data: 2.43-Load-a-DataFrame-with-sensitive-information.mp4 Using MLFlow with Databricks Notebooks: 2.44-mlops-mlflow-tracking.mp4 End to End ML with MLFlow and Databricks: 2.45-end-to-end-ml-with-mlflow-and-databricks.mp4 Comparing DataFrame Libraries between Rust and Python: 2.46-comparing-dataframe-libs-rust-python.mp4 Lesson 3: Data Engineering Libraries and Tools with Rust Parquet file writing and reading with Rust: 2.50-parquet-read-write-rust.mp4 Arrow & Parquet in Rust: 2.51-arrow-parquet-rust.mp4 Serverless functions with Rust and AWS Lambda: 2.52-serverless-rust-aws-lambda.mp4 Polars library overview: 2.53-polars-library-overview.mp4 Building RESTful APIs with Rocket: 2.54-building-restful-apis-rocket.mp4 Utilizing Async Rust in Web Development: 2.55-utilizing-async-rust-web-development.mp4 Applying Data Cleaning Techniques with Rust: 2.56-applying-data-cleaning-rust.mp4 Deploying Rust Applications in a Kubernetes Environment: 2.57-deploying-rust-apps-kubernetes.mp4 Section 4: Designing Data Processing Systems in Rust Lesson 1: Getting Started with Rust Data Pipelines (Including ETL) Jack and the Beanstalk Data Pipelines: 4.1-jack-beanstalk-building-data-pipelines.mp4 Open Source Data Engineering - Pros and Cons: 4.2-open-source-de-pro-con.mp4 Core Components of Data Engineering Pipelines: 4.3-core-components-data-engineering-pipelines.mp4 Rust AWS Step Functions Pipeline: 4.4-rust-aws-step-functions.mp4 Rust AWS Lambda Async S3 Size Calculator: 4.5-rust-async-s3-size-calculator-lambda.mp4 What is Distroless: 4.6-what-is-distroless.mp4 Demo Deploying Rust Microservices on GCP: 4.7-demo-build-deploy-rust-microservice-cloud-run.mp4 Lesson 2: Using Rust and Python for LLMs, ONNX, Hugging Face, and PyTorch Pipelines Introduction to Hugging Face Hub: 4.10-intro-hugging-face-hub.mp4 Rust PyTorch Pre-trained Model Ecosystem: 4.11-rust-pytorch-pretrained-models-ecosystem.mp4 Rust GPU Hugging Face Translator: 4.12-rust-gpu-hugging-face-translator.mp4 Rust PyTorch High-Performance Options: 4.13-high-performance-pytorch-rust-demo.mp4 Rust CUDA PyTorch Stress Test: 4.14-building-cuda-enabled-stress-test-with-rust-pytorch.mp4 EFS ONNX Rust Inference with AWS Lambda: 4.15-efs-onnx-lambda-rust-inference-mlops.mp4 Theory behind model fine-tuning: 4.16-intro-fine-tuning-theory.mp4 Doing Fine Tuning: 4.17-doing-fine-tuning.mp4 Lesson 3: Building SQL Solutions with Rust, Generative AI and Cloud Selecting the correct database on GCP: 4.20-gcp-optimize-database-solution.mp4 Rust SQLite Hugging Face Zero Shot Classifier: 4.21-rust-sqlite-hugging-face-zero-shot-classifier-demo.mp4 Prompt Engineering for BigQuery: 4.22-big-query-prompt-engineering-v3.mp4 Big Query to Colab Pipeline: 4.23-bq-colab-pipeline-v2.mp4 Exploring Data with Big Query: 4.24-exploring-data-google-bigquery-v2.mp4 Using Public Datasets for Data Science: 4.25-using-public-datasets.mp4 Querying Log files with BigQuery: 4.26-demo-big-query-log-query.mp4 There is no one size database: 4.27-one-size-database.mp4 Course Conclusion: 4.28-conclusion.mp4 Learning Objectives By the end of this Course, you will be able to: Leverage Rust's robust data structures and collections for efficient data manipulation. …”

Tabla de Contenidos: “…Quintillas a un fraile quedando la mano a una beata en un mal paso, suspiro por do non deviera, fue asumpto de.. . [Firmado y rubricado] (h . 219 r.-221 r.) . vv.: Musa mía tu me inspira / i me sopla hasta no mas (h . 219 r.) . 148 . …”

“…In the second section, we extended the findings made in section 1. To do that, we carried out a longitudinal study over 80 cows during a complete lactation. …”
Acceso restringido con credenciales UPSA