Category Archives: Generative AI
ChatGPT for Data Science Projects – Examples
Data science is all about turning raw data into actionable insights and outcomes that drive value for your organization. But as any data science professional knows, coming up with new, innovative ideas for your projects is only half the battle. The real challenge is finding a way to turn those ideas into results that can be used to drive business success by doing proper data analysis and building machine learning models using most appropriate algorithms. Unfortunately, many data science professionals struggle with this second step, which can lead to frustration, wasted time and resources, and missed opportunities. That’s where ChatGPT comes in. As a language model trained by OpenAI, ChatGPT …
NLP: Huggingface Transformers Code Examples
Do you want to build cutting-edge NLP models? Have you heard of Huggingface Transformers? Huggingface Transformers is a popular open-source library for NLP, which provides pre-trained machine learning models and tools to build custom NLP models. These models are based on Transformers architecture, which has revolutionized the field of NLP by enabling state-of-the-art performance on a range of NLP tasks. In this blog post, I will provide Python code examples for using Huggingface Transformers for various NLP tasks such as text classification (sentiment analysis), named entity recognition, question answering, text summarization, and text generation. I used Google Colab for testing my code. Before getting started, get set up with transformers …
Andrew Ng & OpenAI ChatGPT Prompt Engineering Course
Renowned artificial intelligence (AI) experts, Andrew Ng from DeepLearning.ai and Isa Fulford from OpenAI, have teamed up to offer an exciting new course on prompt engineering, titled “ChatGPT Prompt Engineering for Developers“. The course, which is completely free, aims to help developers better understand the prompts design and implementation for various use cases. The ChatGPT Prompt Engineering course is specifically tailored for developers including data scientists who wish to learn more about designing prompts for different tasks including software development (coding), marketing, creating product reviews & description, writing essay, summarizing text etc. It includes several important topics such as summarizing, inferring, transforming, expanding and chatbot building. These skills are essential …
ChatGPT Prompts for Focused Learning
Have you ever felt frustrated with the limited time you have to learn and understand key concepts or topics in your desired field in a focused manner? Do you feel lost with the technical terms and jargon used in the desired field? ChatGPT’s prompts can help you overcome these obstacles and make learning more efficient and effective. By leveraging the power of natural language processing and machine learning, ChatGPT provides you with personalized learning opportunities that cater to your specific needs and learning goals. Through this blog, we will explore a list of ChatGPT prompts which can help you learn about any topics in your desired field of interest in …
ChatGPT Prompt for Job Interview Preparation
Preparing for a job interview can be a nerve-wracking experience. It’s natural to feel a sense of pressure as you try to impress your potential employer and secure the job you’ve been dreaming of. However, with the right preparation, you can increase your chances of acing the interview and landing the job. That’s where ChatGPT comes in. As a powerful language model trained by OpenAI, ChatGPT is equipped with the knowledge and expertise to provide you with valuable insights and prompts to help you prepare for your job interview. In this blog, we’ll explore some of the ways that ChatGPT can assist you in your job interview preparation. Whether you’re …
OpenAI’s Business Case Studies & Use Cases
In today’s fast-paced world, businesses are constantly searching for new and innovative ways to stay ahead of the competition and artificial intelligence (AI) is one of the key technology enabler driving innovation and bringing competitive edge. One of the most promising AI technologies in recent years has been generative AI, which has the potential to transform the way companies operate and interact with customers. Among the leading generative AI platforms available today is OpenAI, a pioneer company in the field of generative AI that is dedicated to advancing AI in a safe and beneficial way. In this blog, we will explore OpenAI’s potential case studies and related use cases for …
Amazon Bedrock to Democratize Generative AI
Amazon Web Services (AWS) has announced the launch of Amazon Bedrock and Amazon Titan foundational models (FMs), making it easier for customers to build and scale generative AI applications with foundation models. According to AWS, they received feedback from their select customers that there are a few big things standing in their way today in relation to different AI use cases. First, they need a straightforward way to find and access high-performing FMs that give outstanding results and are best-suited for their purposes. Second, customers want integration into applications to be seamless, without having to manage huge clusters of infrastructure or incur large costs. Finally, customers want it to be …
Generative AI: Scaling Techniques for LLM Models
In the rapidly evolving world of artificial intelligence, large language models (LLMs) have emerged as a game-changing force, revolutionizing the way we interact with technology and transforming countless industries. These powerful models can perform a vast array of tasks, from text generation and translation to question-answering and summarization. However, unlocking the full potential of these LLMs requires a deep understanding of how to effectively scale these LLMs, ensuring optimal performance and capabilities. In this blog post, we will delve into the crucial concept of scaling techniques for LLM models and explore why mastering this aspect is essential for anyone working in the AI domain. As the complexity and size of …
Autoencoder vs Variational Autoencoder (VAE): Differences
In the world of generative AI models, autoencoders (AE) and variational autoencoders (VAEs) have emerged as powerful unsupervised learning techniques for data representation, compression, and generation. While they share some similarities, these algorithms have unique properties and applications that distinguish them from each other. This blog post aims to help machine learning / deep learning enthusiasts gain a deeper understanding of these two methods, their key differences, and how they can be utilized in various data-driven tasks. We will learn about autoencoders and VAEs, understanding their core components, working mechanisms, and common use-cases. We will also try and understand their differences in terms of architecture, objectives, and outcomes. What are …
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