Tag Archives: machine learning
7 Free MIT AI / Machine Learning Courses: Enroll Now!
Are you eager to dive into the world of machine learning and AI but worried about the costs? Are you fascinated by how data analytics can shape the future of various industries? What if you could access top-notch education from one of the leading institutions in the world, absolutely free? In the next six months, MIT is offering seven upcoming free courses designed to equip you with the knowledge and skills in machine learning, AI, and data analytics. Whether you’re a seasoned professional looking to upskill or a beginner ready to embark on a new journey, these courses provide an incredible opportunity. In this blog, we’ll delve into the details …
Pre-training vs Fine-tuning in LLM: Examples
Are you intrigued by the inner workings of large language models (LLMs) like BERT and GPT series models? Ever wondered how these models manage to understand human language with such precision? What are the critical stages that transform them from simple neural networks into powerful tools capable of text prediction, sentiment analysis, and more? The answer lies in two vital phases: pre-training and fine-tuning. These stages not only make language models adaptable to various tasks but also bring them closer to understanding language the way humans do. In this blog, we’ll dive into the fascinating journey of pre-training and fine-tuning in LLMs, complete with real-world examples. Whether you are a …
IIT Madras Fellowship in AI for Social Good
Are you an AI researcher driven by the passion to make a positive impact on society? Do you seek to use your knowledge in machine learning and AI to contribute to real-world issues? Are you intrigued by the idea of joining a leading interdisciplinary research center for data science in India? Then here is the opportunity to discover a unique opportunity that aligns with your aspirations and expertise at the Robert Bosch Centre for Data Science and Artificial Intelligence (RBCDSAI), IIT Madras. Apply Now for fellowship program in AI for social good. About RBCDSAI RBCDSAI is one of India’s pre-eminent interdisciplinary research academic centers specializing in Data Science and AI. …
BERT vs GPT Models: Differences, Examples
Are you intrigued by the world of natural language processing (NLP) and the cutting-edge machine learning models that power it? Have you ever wondered what sets apart two of the most prominent models in the field, Bidirectional Encoder Representations from Transformers (BERT) and Generative Pre-trained Transformer (GPT)? These models have revolutionized the way machines understand and generate human language, but what exactly differentiates them? In this blog, we will delve into the core architecture, training objectives, real-world applications, examples and more. By exploring these aspects, we’ll learn about the unique strengths and use cases of both models, providing you with insights that can guide your next project or research endeavor. …
Generative AI – Concepts, Use Cases, Examples
Machine learning has rapidly evolved over the past few years, with new techniques and methods emerging regularly. One of the most exciting and promising areas in this field is Generative AI. This is also termed as generative modeling. Generative AI or generative modeling refers to the modeling algorithms / methods which results in the creation of new data samples in use cases such as text generation, text summarization, machine translation, image generation etc. This technique has gained immense popularity in recent times due to its ability to generate text, highly realistic images, videos, and music. As a data scientist, it is crucial to understand generative AI / modeling and its …
Machine Learning Projects for Final Year Students: Examples
As aspiring data scientists, computer scientists, and statisticians, the final year of your academic journey presents a perfect opportunity to showcase your skills and knowledge in practical applications. In this blog, we will explore a diverse set of exciting machine-learning projects that are well-suited for final-year students. These projects cover various domains, including education, healthcare, crime prediction, and more. We will delve into each project’s description, problem type (classification, regression, etc.), and the methods used for analysis. Whether you are seeking inspiration for your final year project or simply eager to explore the power of machine learning in real-world scenarios, this blog has something for everyone! In case you would …
Exploring Amazon Science Publications: A Quick Guide
In the ever-evolving world of technology and research, staying updated with the latest advancements is crucial. Amazon Science Publications has emerged as a treasure trove for those hungry for knowledge, offering a plethora of articles that span a wide range of topics. Whether you’re an AI / ML researcher, a student, or just a curious mind, this platform has something for everyone. Let’s delve into the vast ocean of articles available on Amazon Science Publications. Research Areas: Tags: Conferences: Journals: Date: Whether you’re looking for the latest articles from 2023 or want to revisit the gems from 2015, Amazon Science Publications has got you covered. With articles spanning from 2015 …
Retrieval Augmented Generation (RAG) & LLM: Examples
Have you ever wondered how to seamlessly integrate the vast knowledge of Large Language Models (LLMs) with the specificity of domain specific knowledge or external databases? As the world of machine learning continues to evolve, the need for more sophisticated and contextually relevant responses from models becomes paramount. For data scientists and product managers keen on deploying LLMs in production, the Retrieval Augmented Generation (RAG) pattern offers a compelling solution. In this blog, we’ll dive deep into the RAG pattern, illustrating its power and potential with practical examples. Whether you’re aiming to enhance your product’s AI capabilities or simply curious about the next big thing in machine learning, this exploration …
Greedy Search vs Beam Search Decoding: Concepts, Examples
Have you ever wondered how machine learning models transform their intricate calculations into clear, human-readable language? Or how your smartphone knows exactly what you’re going to type next before you even start typing? These everyday marvels are powered by a critical component of natural language processing (NLP) known as ‘decoding methods‘. But how do these methods work, and why are there different types? In the vast field of machine learning, a primary challenge in natural language processing tasks is converting a model’s computational output into an understandable and coherent text. Whether it’s autocompleting your sentences, translating text from one language to another, or generating a news article, these tasks involve …
NPTEL’s Machine Learning & Data Science Online Courses (Jul-Nov 2023)
In the rapidly evolving domains of Machine Learning, Data Science, and Artificial Intelligence, the quest for quality education and courses has become paramount. For those familiar with the educational landscape of India, the Indian Institutes of Technology (IITs) stand out as beacons of excellence. Established by the government of India, the IITs are autonomous public technical universities that are recognized globally for their outstanding curriculum, research, and innovation. Every year, thousands of students vie for a coveted spot in these institutions, and their alumni have made significant contributions to technology and research worldwide. NPTEL (National Programme on Technology Enhanced Learning), in collaboration with these premier IITs, has curated a range …
Vanishing Gradient Problem in Deep Learning: Examples
Ever found yourself wondering why your deep learning (deep neural network) model is simply refusing to learn? Or struggled to comprehend why your deep neural network isn’t reaching the accuracy you expected? The culprit behind these issues might very well be the infamous vanishing gradient problem, a common hurdle in the field of deep learning. Understanding and mitigating the vanishing gradient problem is a must-have skill in any data scientist‘s arsenal. This is due to the profound impact it can have on the training and performance of deep neural networks. In this blog post, we will delve into the heart of this issue, learning the calculus behind neural networks and …
DCGAN Architecture Concepts, Real-world Examples
Have you ever wondered how AI can create lifelike images that are virtually indistinguishable from reality? Well, there is a neural network architecture, Deep Convolutional Generative Adversarial Network (DCGAN) that has revolutionized image generation, from medical imaging to video game design. DCGAN’s ability to create high-resolution, visually stunning images has brought it into great usage across numerous real-world applications. From enhancing data augmentation in medical imaging to inspiring artists with novel artworks, DCGAN‘s impact transcends traditional machine learning boundaries. In this blog, we will delve into the fundamental concepts behind the DCGAN architecture, exploring its key components and the ingenious interplay between its generator and discriminator networks. Together, these components …
Autoregressive (AR) Models Python Examples: Time-series Forecasting
Autoregressive (AR) models, which are used for text generation tasks and time series forecasting, can be employed to predict future values predicated on previous observations. This blog post will provide the concepts of autoregressive (AR) models with Python code examples to demonstrate how you can implement an AR model for time-series forecasting. Note that time-series forecasting is one of the important areas of data science/machine learning. In subsequent blogs, we will take up the topic of how autoregressive models can be used as generative model for text generation tasks. For beginners, time-series forecasting is the process of using a model to predict future values based on previously observed values. Time-series data …
GAN vs VAE: Differences, Similarities, Examples
Are you curious about how machines not only learn from data but actually create it? Have you ever found yourself puzzled while trying to choose between Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) for your project? Or, even trying to understand when to use GANs or VAEs? Well, you’re not alone! In this blog post, we’re going to learn about two key technologies GANs vs VAEs in the generative modeling, comparing their strengths, weaknesses, and everything in between. We will dive into real-life scenarios, showing when you might want to pull out GANs to generate high-quality, realistic images, and when you’d prefer the control that VAEs provide over the …
Large Language Models (LLMs) & Semantic Search
Ever scratched your head wondering how a few typed words can bring up the precise information you need from the sprawling web? That’s the work of something called Large Language Models or LLMs, like the GPT-series from OpenAI. These large language models (LLMs) can be used to search that needle-in-a-haystack piece of information you’re after. So, how do they do it? They use smart techniques like Dense Retrieval, Reranking, and Generative Search. In this blog, you will learn about these great techniques in an easy-to-understand way. Dense Retrieval Dense retrieval is a departure from traditional information retrieval approaches that often rely on sparse features like Bag-of-Words (BoW) and Term Frequency-Inverse …
Generative Adversarial Network (GAN): Concepts, Examples
In this post, you will learn concepts & examples of generative adversarial network (GAN). The idea is to put together key concepts & some of the interesting examples from across the industry to get a perspective on what problems can be solved using GAN. As a data scientist or machine learning engineer, it would be imperative upon us to understand the GAN concepts in a great manner to apply the same to solve real-world problems. This is where GAN network examples will prove to be helpful. What is Generative Adversarial Network (GAN)? We will try and understand the concepts of GAN with the help of a real-life example. Imagine that …
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