How to Access GPT-4 using OpenAI Playground?
How good it would be if we could access GPT-4 using the OpenAI Playground and harness the groundbreaking advancements OpenAI has made in generating human-like text? OpenAI has revolutionized the field of natural language processing (NLP) with its large language models (such as different versions of GPT-3.5), and the release of GPT-4 has further pushed the boundaries of what’s achievable. In this blog post, we will guide you through a step-by-step process to access GPT-4 model using the OpenAI playground. Step 1: Visit the OpenAI Playground To get started, open your web browser and navigate to the OpenAI Playground website. The URL for the OpenAI Playground is https://playground.openai.com/. Step 2: …
Online US Degree Courses & Programs in AI / Machine Learning
Data Science & AI / Machine learning has emerged as a transformative field, revolutionizing industries and shaping the future of technology. As the demand for professionals skilled in machine learning continues to rise, top universities in the United States (USA) have recognized the need to offer online degree courses and programs in this dynamic field. Through these online offerings, students can now access world-class education and earn prestigious degrees from the comfort of their own homes, while benefiting from the expertise of renowned faculty members. In this blog post, we present a curated list of leading US universities that provide online degree courses and programs in machine learning. Whether you …
AIC & BIC for Selecting Regression Models: Formula, Examples
When working with regression models, selecting the most appropriate machine learning model is a critical step toward understanding the relationships between variables and making accurate predictions. With numerous regression models available, it becomes essential to employ robust criteria for model selection. This is where the two most widely used criteria come to the rescue. They are the Akaike Information Criterion (AIC) and the Bayesian Information Criterion (BIC). In this blog, we will learn about the concepts of AIC, BIC and how they can be used to select the most appropriate machine learning regression models. AIC & BIC Concepts Explained with Formula In model selection for regression analysis, we often face …
Azure OpenAI Service Details & Pricing Info
Azure OpenAI, an offering from Microsoft Azure, empowers developers, researchers, and enterprises with the transformative capabilities of Artificial Intelligence (AI). In this blog post, we explore Azure OpenAI’s service details and pricing information, providing you with insights to harness the immense power of AI. Azure OpenAI Services Information Azure OpenAI service provides a range of large language models from standard machine learning models to fine-tuned ones for specific tasks. We can build intelligent chatbots, automate code generation, or enhance natural language understanding. We can leverage conversational AI models for interactive virtual assistants that elevate user experiences and streamline operations. Image generation models can be used to produce stunning, realistic visuals. …
Recommender Systems in Machine Learning: Examples
Recommender systems are used in machine learning to predict the ratings or preferences of items for a given user. They are commonly used in e-commerce applications to suggest items that a user may be interested in. One common example of a recommender system is Netflix. Netflix uses a recommender system to suggest movies and TV shows that a user may want to watch. The algorithm looks at past ratings and preferences to make suggestions. In this blog post, you will learn about recommender systems and some of the different types of recommender systems with the help of examples. Recommender systems make use of machine learning to predict the ratings or …
Binomial Distribution Explained with Examples
Have you ever wondered how to predict the number of successes in a series of independent trials? Or perhaps you’ve been curious about the probability of achieving a specific outcome in a sequence of yes-or-no questions. If so, we are essentially talking about the binomial distribution. It’s important for data scientists to understand this concept as binomials are used often in business applications. The binomial distribution is a discrete probability distribution that applies to binomial experiments (experiments with binary outcomes). It’s the number of successes in a specific number of trials. Sighting a simple yet real-life example, the binomial distribution may be imagined as the probability distribution of a number …
Online Data Science Courses at JHU 2023
Are you interested in pursuing a Data Science course from the comfort of your own home? Look no further than Johns Hopkins University (JHU), offering a comprehensive range of Online Data Science Courses for the year 2023. Whether you are a working professional seeking to enhance your skills or a student looking to delve into the exciting world of data science, JHU’s online programs provide the flexibility and quality education you need. In this blog, we will explore the diverse array of online courses available at JHU, designed to cater to remote learners who want to excel in the field of Data Science. Discover the cutting-edge curriculum, esteemed faculty, and …
Model Cards Example Machine Learning
Have you ever wondered how to make your machine learning models more transparent, understandable, and accountable? Are you looking to implement responsible AI practices including ways and means to review and improve your existing model documentation? If so, you will learn about the concept of model cards, a powerful tool for documenting important details about machine learning models. You will learn the concepts with concrete examples and best practices that can serve as a guide for implementing or improving model cards in your organizations. The model card example can be seen as an standard template for model card which gets used in various different companies such as Google. What are …
Difference between Data Science & Data Analytics
What’s the difference between data science and data analytics? Many people use these terms interchangeably, but there is a big distinction between the two fields. Data science is more focused on understanding and deriving insights from data while leveraging statistical and machine learning methods, while data analytics is an overarching term used to solve problems using analytical techniques while leveraging data. Both the terms are in a way related. In this blog post, we’ll explore the differences between data science and data analytics in greater detail, with examples of each. The following are key topics in relation to the difference between data science and data analytics: Different forms/purposes Different techniques …
Top US Universities for AI / ML Research
Artificial Intelligence (AI) has become an essential driver of innovation and economic growth in the 21st century. As a result, some of the best universities in the United States have been investing heavily in AI research to push the boundaries of this rapidly evolving field. In this blog post, we will explore the top 10 US universities for AI research, highlighting their achievements and providing links to their AI research homepages. Several leading / best universities in the United States have emerged as pioneers in AI research, recognizing its crucial role in driving innovation and economic growth. These institutions have made significant investments to establish themselves as top destinations for …
LLM Chain OpenAI Python Example
Have you ever wondered how to fully utilize large language models (LLMs) in our natural language processing (NLP) applications, like we do with ChatGPT? Would you not want to create an application such as ChatGPT? While learning to make a direct API call to an OpenAI LLMs is a great start, we can build full fledged applications serving our end user needs. And, building prompts that adapt to user input dynamically is one of the most important aspect of the NLP app. That’s where LangChain, a powerful framework, comes in. In this blog, we will delve into the concept of LangChain and showcase its usage through a practical example of …
Linear Regression T-test: Formula, Example
Linear regression is a popular statistical method used to model the relationship between a dependent variable and one or more independent variables. In linear regression, the t-test is a statistical hypothesis testing technique that is used to test the hypothesis related to linearity of the relationship between the response variable and different predictor variables. In this blog, we will discuss linear regression and t-test and related formulas and examples. For a detailed read on linear regression, check out my related blog – Linear regression explained with real-life examples. T-tests are used in linear regression to determine if a particular variable is statistically significant in the model. A statistically significant variable …
Langchain ChatGPT Hello World Python Example
Have you ever wondered how to build applications that not only utilize large language models (LLMs) but are also capable of interacting with their environment and connecting to other data sources? If so, then LangChain is the answer! In this blog, we will learn about what is LangChain, what are its key aspects, how does it work. We will the learn about creating a ‘Hello World’ Python program using LangChain and OpenAI’s Language Learning Model (LLM). What is LangChain Framework? LangChain is a dynamic framework specifically designed for the development of such applications. The unique aspect of LangChain is that it encourages the creation of applications that are “data-aware” and …
When to Use Z-test vs T-test: Differences, Examples
When it comes to statistical tests, z-test and t-test are two of the most commonly used. But what is the difference between z-test and t-test? And when should you use Z-test vs T-test? In this blog post, we will answer all these questions and more! We will start by explaining the difference between z-test and t-test in terms of their formulas. Then we will go over some examples so that you can see how each test is used in practice. As data scientists, it is important to understand the difference between z-test and t-test so that you can choose the right test for your data. Let’s get started! Difference between …
Hold-out Method for Training Machine Learning Models
The hold-out method for training the machine learning models is a technique that involves splitting the data into different sets: one set for training, and other sets for validation and testing. The hold-out method is used to check how well a machine learning model will perform on the new data. In this post, you will learn about the hold-out method used during the process of training the machine learning model. Do check out my post on what is machine learning? concepts & examples for a detailed understanding of different aspects related to the basics of machine learning. Also, check out a related post on what is data science? When evaluating …
How to Choose Right Statistical Tests: Examples
Whether you are a researcher, data analyst, or data scientist, selecting the appropriate statistical test is crucial for accurate and reliable data analysis. With numerous tests available, it can be overwhelming to determine the right one for your research question and data type. In this blog, the aim is to simplify the process, providing you with a systematic approach to choosing the right statistical test. This blog will be particularly helpful for those who are new to statistical analysis and are unsure which test to use for their specific needs. You will learn a clear and structured method for selecting the appropriate statistical test. By considering factors such as data …