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It's a great time to break into data engineering. So where do you start?
Learning data engineering can sometimes feel overwhelming because of…
Deep convolutional neural networks (DCNNs) have been a game-changer for several computer vision tasks. These include object identification, object recognition, image segmentation, and edge detection. The ever-growing size and power…
How to know the unknowable in observational studies Introduction Problem Setup 2.1. Causal Graph 2.2. Model With and Without Z 2.3. Strength of Z as a Confounder Sensitivity Analysis 3.1.…
In the age of relentless technological advancement, artificial intelligence has emerged as the unsung hero, revolutionizing industries one algorithm at a time. Among the sectors witnessing a seismic shift, the…
It’s no secret that supervised machine learning models need to be trained on high-quality labeled datasets. However, collecting enough high-quality labeled data can be a significant challenge, especially in situations…
The emergence of Large Vision-Language Models (LVLMs) characterizes the intersection of visual perception and language processing. These models, which interpret visual data and generate corresponding textual descriptions, represent a significant…
Automation, machine learning and LLMs in the chip industry (source: chatGPT)I felt like one of those guys from Monsters Inc. You know, the ones in the big yellow hazmat suits.…
Optical character recognition (OCR) software help convert non-editable document formats such as PDFs, images, or paper documents into machine-readable formats that are editable & searchable. OCR applications are commonly used…
Diffusion models are a set of generative models that work by adding noise to the training data and then learn to recover the same by reversing the noising process. This…
How to Create a Speech-to-Text-to-Speech Program Image by Mariia Shalabaieva from unsplashIt’s been exactly a decade since I started attending GeekCon (yes, a geeks’ conference 🙂) — a weekend-long hackathon-makeathon…