MLOps Tools: MLflow and Hugging Face

Colleagues, the MLOps Tools: MLflow and Hugging Face course covers two of the most popular open source platforms for MLOps (Machine Learning Operations): MLflow and Hugging Face. We’ll go through the foundations on what it takes to get started in these platforms with basic model and dataset operations. You will start with MLflow using projects and models with its powerful tracking system and you will learn how to interact with these registered models from MLflow with full lifecycle examples. Then, you will explore Hugging Face repositories so that you can store datasets, models, and create live interactive demos. By the end of the course, you will be able to apply MLOps concepts like fine-tuning and deploying containerized models to the Cloud. This course is ideal for anyone looking to break into the field of MLOps or for experienced MLOps professionals who want to improve their programming skills. {Duke University}

Enroll today (teams & executives are welcome): https://tinyurl.com/5n9ysv36 

Download your free AI-ML-DL - Career Transformation Guide.

Listen to the ChatGPT audiobook on Audible. (https://tinyurl.com/bdfrtyj2) or read the ebook today on Amazon Kindle. (https://tinyurl.com/jfntsyj2) 

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (share with your team)

AI Software Engineer: ChatGPT, Bard and Beyond (Interview Prodigy book series)

Colleagues, the purpose of the “AI Software Engineer: ChatGPT, Bard and Beyond” (audiobook & ebook) help software engineers and developers capture their ideal job offer and manage their medium-to-long-term career growth in the global artificial intelligence arena. We will focus on artificial intelligence software engineers and developers in this series. Artificial intelligence has proven to be a revolutionary part of the digital era. As a result, top tech giants like Amazon, Google, Apple, Facebook, Microsoft, and International Business Machines Corporation have been investing significantly in the research and development of artificial intelligence. As a result, these companies are contributing well to making A.I. more accessible for businesses. In addition, different companies have adopted A.I. technology for improved customer experience. For example, in March 2020, McDonald's invested $300 million to acquire an A.I. startup in Tel Aviv to provide a personalized experience for its customers using artificial intelligence. This was its most significant tech investment.

AI Engineers have many opportunities, which will only grow with time. After reading this book, I hope you can identify your ideal job offer and manage your short- and long-term career growth plan, especially in artificial intelligence. The world of artificial intelligence is vast. As I stated earlier in this book, it has a current market size of $136.55 billion based on a 2022 report by CAGR, and it will likely reach a growth rate of 37.3% from 2023 to 2030. You can study artificial intelligence from three aspects. First, the narrow artificial intelligence: this is where you learn about strong AI, artificial general intelligence, and narrow artificial intelligence, also known as weak AI. As I mentioned earlier in this book, the tech we use daily is known as narrow artificial intelligence mainly because it focuses on one narrow task. An example is a chess computer, Siri, or Alexa. Artificial narrow intelligence generally operates within a limited predetermined range. Then there is machine learning, an application that allows systems and computers to learn and improve without being programmed. This idea aims to enable systems to learn and adapt automatically without human involvement or support. Deep learning enables inventors to enhance technology such as self-driving vehicles, speech recognition, and facial identification.

Audible (https://tinyurl.com/28pjupkb)  (Audible)

Kindle eBook: (https://tinyurl.com/2juy37n4)  (Kindle) 

Series: “The Interview Prodigy”

Regards, Genesys Digital (Amazon Author Page) https://tinyurl.com/hh7bf4m9 

Artificial Intelligence-Machine Learning-Deep Learning - Career Transformation Guide (2023 V1)

Colleagues, the new Artificial Intelligence-Machine Learning-Deep Learning - Career Transformation Guide includes valuable information that enables you to accelerate your career growth and income potential - Career opportunities, Salaries (demand and growth), Certifications and Training programs, Publications and Portals along with Professional Forums and Communities. The Certification and Training programs are categorized by Artificial Intelligence, Machine Learning, Deep Learning, Natural Language Processing and Computer Vision.

Grand View Research’s Artificial Intelligence Market Size & Share Analysis Report 2030 projects “The global artificial intelligence market size was valued at USD 136.55 billion in 2022 and is projected to expand at a compound annual growth rate (CAGR) of 37.3% from 2023 to 2030. The continuous research and innovation directed by tech giants are driving the adoption of advanced technologies in industry verticals, such as automotive, healthcare, retail, finance, and manufacturing.”  These data are affirmed in the World Economic Forum bellwether article “The future of jobs in the age of AI, sustainability and deglobalization” (May 2023). This article is a must-read for executives and mid-level professionals alike.

Download your free AI-ML-DL - Career Transformation Guide (2023 v1).

New audio & ebook: “ChatGPT - The Era of Generative Conversational AI Has Begun” (Audible) (Kindle) 

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (share with your team) 

Build, Train, and Deploy Machine Learning Pipelines using BERT

Coleagues, Build, Train, and Deploy Machine Learning Pipelines using BERT: Learn to automate a natural language processing task by building an end-to-end machine learning pipeline using Hugging Face’s highly-optimized implementation of the state-of-the-art BERT algorithm with Amazon SageMaker Pipelines. Your pipeline will first transform the dataset into BERT-readable features and store the features in the Amazon SageMaker Feature Store. It will then fine-tune a text classification model to the dataset using a Hugging Face pre-trained model, which has learned to understand the human language from millions of Wikipedia documents. Finally, your pipeline will evaluate the model’s accuracy and only deploy the model if the accuracy exceeds a given threshold. Practical data science is geared towards handling massive datasets that do not fit in your local hardware and could originate from multiple sources. One of the biggest benefits of developing and running data science projects in the cloud is the agility and elasticity that the cloud offers to scale up and out at a minimum cost. The Practical Data Science Specialization helps you develop the practical skills to effectively deploy your data science projects and overcome challenges at each step of the ML workflow using Amazon SageMaker. This Specialization is designed for data-focused developers, scientists, and analysts familiar with the Python and SQL programming languages and want to learn how to build, train, and deploy scalable, end-to-end ML pipelines - both automated and human-in-the-loop - in the AWS cloud. {AWS & DeepLearning.AI}

Access this new ebook today on Amazon Kindle. (https://tinyurl.com/jfntsyj2) 

Listen to the audiobook on Audible. (https://tinyurl.com/bdfrtyj2) 

Or read our series on “Transformative Innovation”. (https://tinyurl.com/3habrwrv) 

Become a new AudibleListener® member on Amazon Audible (https://www.audible.com) 

Read the OpenAI ChatGPT 4 - Technical Report. (https://arxiv.org/pdf/2303.08774.pdf) 

Download your free AI-ML-DL - Career Transformation Guide.

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (share with your team)

ChatGPT and Generative AI: The Big Picture

AI colleagues, in this “ChatGPT and Generative AI: The Big Picture” program you will learn the basics of generative AI, how it works, and how to apply ChatGPT to real-world problems. ChatGPT and generative AI are all the rage, and have the potential to transform how we work, learn, and interact. But how do you cut through all the hype? In this course, ChatGPT and Generative AI: The Big Picture, you’ll get a foundational understanding of these powerful new technologies. First, you'll explore generative AI and how it works to create human-like responses to questions. Next, you’ll discover ChatGPT and see several examples of its capabilities, as well as some limitations. Finally, you’ll learn how ChatGPT can be applied to real-world applications, including day-to-day use cases for data practitioners. When you’re finished with this course, you’ll have a practical understanding of ChatGPT and how you can use it to work smarter, not harder. Training modules address: 1) What Are ChatGPT and Generative AI?, 2) Getting Started with ChatGPT, 3) Applying ChatGPT to the Real World, and 4) ChatGPT Use Cases for Data Practitioners.

Register today at: https://tinyurl.com/ms5e97nn (teams & execs are welcome)

Read the OpenAI ChatGPT 4 - Technical Report. (https://arxiv.org/pdf/2303.08774.pdf) 

Listen to the new audiobook “ChatGPT: The Era of Generative Conversational AI Has Begun” on Audible. (https://tinyurl.com/bdfrtyj2) or read via Amazon Kindle. (https://tinyurl.com/jfntsyj2) 

Download your free AI-ML-DL - Career Transformation Guide.

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (share with your team)

Artificial Intelligence Essentials: AI-based Chatbots

Colleagues, the “Artificial Intelligence Essentials: AI-based Chatbots” program will teach you what AI Chatbots are by understanding how they differ from regular chatbots and what are good use cases You have probably come across chatbots when browsing online. You might notice some are a bit more equipped than others. Some of these well-equipped ones might have been an AI-based chatbot. In this course, Artificial Intelligence Essentials: AI-based Chatbots, you will gain the ability to Evaluate AI-based chatbots. First, you will explore what the foundation of AI-based chatbots are and how they perform. Next, you will discover how AI-based chatbots can be used in modern day products by going through different use cases of AI-based chatbots. Finally, you will learn what applications are available to create an AI-based chatbot. By the end of this course, you will have the skills and knowledge of AI-based chatbots and how to use them in your own environment. Training modules include: 1) Evaluating AI Based Chatbots - What Is a Chatbot? Types of Chatbots, Examples of AI Based Chatbots, 2) Understanding AI Based Chatbots - Components of an AI Chatbot, What Is Natural Language Processing?, What Is a Knowledge Base?, Understanding Intent, 3) Describing Applications of AI Based Chatbots - Industry Use of AI Chatbots, Demo: Retail Chatbot, 4) Using Tools to Create an AI based Chatbots - Tools to Built an AI Chatbot, SDK and API for AI Chatbots, Demo: Using ChatGPT with OpenAI API via Code, AI Chatbot Builders, Demo: AI Chatbot with Azure Cognitive Question Answering. 

Enroll today: https://pluralsight.pxf.io/WqO0KX (teams & executives are welcome)

Read the OpenAI ChatGPT 4 - Technical Report. (https://arxiv.org/pdf/2303.08774.pdf) 

Download your free AI-ML-DL - Career Transformation Guide.

Listen to the ChatGPT audiobook on Audible. (https://tinyurl.com/bdfrtyj2) or read the ebook today on Amazon Kindle. (https://tinyurl.com/jfntsyj2) 

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (share with your team)

Prompt Engineering for ChatGPT

ChatGPT and other large language models are going to be more important in your life and business than your smartphone, if you use them right. ChatGPT can tutor your child in math, generate a meal plan and recipes, write software applications for your business, help you improve your personal cybersecurity, and that is just in the first hour that you use it. This course will teach you how to be an expert user of these generative AI tools. The course will show amazing examples of how you can tap into these generative AI tools' emergent intelligence and reasoning, how you can use them to be more productive day to day, and give you insight into how they work. Large language models respond to instructions and questions posed by users in natural language statements, known as “prompts”. Although large language models will disrupt many fields, most users lack the skills to write effective prompts. Expert users, who understand how to write good prompts, are orders of magnitude more productive and can unlock significantly more creative uses for these tools. This course introduces students to the patterns and approaches for writing effective prompts for large language models. Anyone can take the course and the only required knowledge is basic computer usage skills, such as using a browser and accessing ChatGPT. Students will start with basic prompts and build towards writing sophisticated prompts to solve problems in any domain. By the end of the course, students will have strong prompt engineering skills and be capable of using large language models for a wide range of tasks in their job, business, personal life, and education, such as writing, summarization, game play, planning, simulation, and programming. {Coursera}

Enroll today:  Prompt Engineering for ChatGPT

Download your complimentary AI-ML-DL - Career Transformation Guide.

Much career success, Lawrence E. Wilson - Artificial Intelligence Academy (share with your team) 

The Promise of Data-Driven Decision Making - From Analytics to Visualization and Beyond (new audiobook & ebook)

Colleagues, “The Promise of Data-Driven Decision Making” is a powerful resource that has the potential to transform the way we approach problem-solving in both our personal and professional lives. By collecting and analyzing data, we can gain valuable insights into the world around us, and use that knowledge to make more informed decisions. Throughout this e-book, we have explored the various aspects of data-based decision making, including the benefits, challenges, and best practices. We have also examined the different tools and techniques that can be used to collect and analyze data, as well as the ethical considerations that must be taken into account.

Highly data-driven firms are three times more likely to report a major improvement in decision making, according to a large decision survey conducted by PWC. However, only one in three CEOs claim that their company is heavily data-driven. It comes up frequently in meetings with corporate leaders that executives have instant access to large volumes of data. We also learn that their personal intuition or gut feeling plays a significant role in their decision-making. How might the art and science of decision-making be combined better? A more efficient use of data and the capacity to draw insights are seen to present potential for enterprises to generate higher value. Analytics may support an organization's growth and innovation, increase productivity, and improve risk management when they are integrated into the culture of decision-making within the company. The use of facts, metrics, and data to inform strategic business decisions that are in line with a company's goals, objectives, and activities is known as data-driven decision-making. Interactive dashboards, work management platforms, and OKR tools are examples of modern analytics tools that assist individuals overcome prejudice and make the best management decisions that are in line with business strategies. Instead of making decisions based on intuition, opinion, or personal experience, it compiles historical data to examine trends and make better decisions for the future in relation to what has previously worked.

Listen today via Amazon Audible (https://tinyurl.com/ydbyh2t9) 

Or read now on Kindle (https://tinyurl.com/hptundzs) 

This book is part of the “Data-Driven Organizations” series.

Much success, Genesys Digital (share with your team) 

“Implementing Data Science Methodology” (new ebook & audiobook)

Colleagues, the new ebook entitled “Implementing Data Science Methodology … From Data Wrangling to Data Viz and Everything in Between” will enable you to lead data science initiatives within your organization. They allow organizations to make informed decisions based on data, which can lead to better results and increased competitiveness. Data-driven methodologies also help organizations to identify areas for improvement and to make more accurate predictions about future outcomes and improve the accuracy of decision-making. By analyzing large amounts of data, organizations can identify patterns and trends that would not be apparent otherwise. This allows them to make more informed decisions, reducing the risk of making decisions based on inaccurate or incomplete information. The implementation of data-driven methodologies is critical for organizations looking to remain competitive in today’s data-driven world. By leveraging data to make informed decisions, organizations can improve their performance, reduce risks, and provide better experiences for their customers. It is important for organizations to invest in the resources and processes needed to implement these methodologies effectively, and to stay up-to-date with the latest trends and technologies in data science. Key topics addressed include: 1) Data-Driven Methodologies, 2) The Role of the Data Scientist, 3) Stakeholders and Buy-in, 4) Key Concepts of Data-Driven Methodology, 5) Data-Driven Lifecycle, 6) Data-driven Roadmapping, 6) Planning and Implementing a Data-Driven Strategy, 7) Data-Driven Predictive Modeling, 8) Business Transformation, and 9) Examples of Data-Driven Organizations.

Read this new ebook today on Amazon Kindle: https://www.amazon.com/dp/B0BWVHSM4N 

Access & listen on Amazon Audible: https://tinyurl.com/mt3xs4ys 

This book is part of the “Data-Driven Organizations” series: https://tinyurl.com/4j49m4zm 

Much success, Genesys Digital (share with your team)