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) 

The Promise of Data-Driven Decision Making - From Analytics to Visualization and Beyond (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.

Access this new ebook today on Amazon Kindle.

And download your free Data Science - Career Transformation Guide.

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

Implementing Data Science Methodology (ebook)

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.

Access this new ebook on the Amazon Kindle today.

And download your free Data Science - Career Transformation Guide.

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

AI Software Engineer - ChatGPT, Bard … and Beyond (ebook)

Colleagues, this new ebook “AI Software Engineer - ChatGPT, Bard … and Beyond” aims to help Software Engineers and Developers capture their ideal job offer and manage their medium-to-long-term career growth in the global Artificial Intelligence (AI) arena. First, we will look at the global market overview for AI Globally. The artificial intelligence (AI) market size was valued at around $136.55 billion in 2022 (Grand View Research, 2022). Also, it was projected to have a compound annual growth rate (CAGR) of 37.3% from 2023 to 2030. if you're interested in AI, you should be familiar with and have expertise with at least one of the following programming languages: Python, C/C++, MATLAB. According to Indeed, salaries for artificial intelligence professionals often range from $99,568 for a full-stack developer to $142,318 for a data scientist. Glassdoor reports the annual average base salary for artificial intelligence professionals in the US is $120,048. Based on a Talent.com report, the average artificial intelligence salary is $143,054 annually. Entry positions start at $115,000, and experienced employees can earn up to $200,000 yearly. 

Access this new ebook on the Amazon Kindle today.

And download your free AI-ML-DL - Career Transformation Guide.

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

ChatGPT … ChatGPT, Bard and Beyond

Colleagues, Generative conversational AI has the potential to improve accessibility for people with disabilities and those who struggle with language barriers, as AI models can be trained to understand and respond to a wide range of languages and dialects. Generative conversational AI represents a major shift in how we interact with technology and has the potential to improve many aspects of our lives, from customer service and support to healthcare and accessibility. Check out this new ebook!

ChatGPT is a specific implementation of Generative conversational AI technology developed by OpenAI. It is a large language model trained on vast text data, allowing it to generate human-like responses to text inputs. In the context of conversational AI, ChatGPT can be used to build chatbots, virtual assistants, and other applications that require the ability to generate text in real time. The model's size and training data allow it to develop highly relevant and human-like text, making it well-suited for various applications. As a state-of-the-art Generative conversational AI, ChatGPT is the perfect tool for organizations looking to step up their communication game. Whether you want to improve interactions with customers, employees, or other stakeholders, ChatGPT makes it easy. Want to see just how much you can achieve with this powerful tool? 

Access this new ebook from the Amazon Kindle Store today: https://tinyurl.com/5yfwvh8a 

And download your free AI-ML-DL - Career Transformation Guide.

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