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Top Important Computer Vision Papers for the Week from 01/01 to 07/01
Author(s): Youssef Hosni Originally published on Towards AI. Stay Updated with Recent Computer Vision Research Every week, several top-tier academic conferences and journals showcased innovative research in computer vision, presenting exciting breakthroughs in various subfields such as image recognition, vision model optimization, …
Fast and Efficient Model Finetuning using the Unsloth Library
Author(s): Eduardo Muñoz Originally published on Towards AI. Image generated by the author on Leonardo.ai Introduction Recently a new framework or library to optimize the training and fine-tuning stage of a large language model has been released: Unsloth. This library is a …
Microsoft Phi-2: Tiny Mighty Open Source Model with Verbal Diarrhea
Author(s): Dr. Mandar Karhade, MD. PhD. Originally published on Towards AI. A new lightweight model for developing prototypes The Phi-2 model, developed by Microsoft, is a 2.7 billion-parameter language model that has recently gained attention in the field of natural language processing …
A Swift Introduction to Deep Learning with PyTorch and TensorFlow
Author(s): Günter Röhrich Originally published on Towards AI. Stepping through theory, background, and code examples Neural networks have gained incredible attention over the last decade (despite being around for much longer), and seem to have made incredible progress in the eyes of …
Categorical Encoding for Time Series: Embracing Dynamic and Meaningful Techniques
Author(s): Alexandre Warembourg Originally published on Towards AI. Let’s move beyond static encoding methods and explore dynamic, meaningful techniques for high-cardinality categorical variables.source: Image generated by Dall-E from Author prompt The categorical data type is data divided by several modalities; let’s take …
A Long-Term Demand Forecasting Model Implementation Case Study with a Major Retailer
Author(s): Alexandre Warembourg Originally published on Towards AI. Explore how I developed a core demand forecasting algorithm for ten countries, dealing with an average product sales history of 11 months and 30% new products in each batch. source : Dall-E generated picture …
How To Create Multiline Synthetic Images Using Synthtiger
Author(s): Eivind Kjosbakken Originally published on Towards AI. Making synthetic data is one of the quickest ways of acquiring a labeled dataset for supervised learning. Instead of labeling files yourself, you already have the ground truth as you are creating the images. …
How To Analyze Data Like a Pro Without Coding?
Author(s): Shreepada Rao Originally published on Towards AI. Leveraging Databricks assistant and Copilot for your day-to-day tasks to boost productivityImage by author: Databricks Assistant “With our new copilot for work, we’re giving people more agency and making technology more accessible through the …
How to Train a Custom Faster RCNN Model In PyTorch
Author(s): Dr. Leon Eversberg Originally published on Towards AI. Fine-tuning a pre-trained Faster RCNN model with custom images in the COCO data format using PyTorchTraining and validation loss during model training. Source: Author In this PyTorch tutorial for beginners, we will use …
Practical Nuances of Time Series Forecasting — Part II— Improving Forecast Accuracy
Author(s): Santoshkumarpuvvada Originally published on Towards AI. Practical Nuances of Time Series Forecasting — Part II— Improving Forecast Accuracy In continuation of enhancing our understanding of time series forecasting, let’s get started with part 2. (Check out the part 1 here). Many …
Google Gemini: The AI model by Google
Author(s): Manika Nagpal Originally published on Towards AI. Google’s launch of Gemini, proclaimed as a groundbreaking AI model and their most potent yet, signals a continued surge in AI advancements. Despite AI's exceptional year since ChatGPT’s debut, the momentum shows no signs …
Google Gemini: The AI model by Google
Author(s): Manika Nagpal Originally published on Towards AI. Google’s launch of Gemini, proclaimed as a groundbreaking AI model and their most potent yet, signals a continued surge in AI advancements. Despite AI's exceptional year since ChatGPT’s debut, the momentum shows no signs …
Checking For Train, Test, Split Success
Author(s): Adam Ross Nelson Originally published on Towards AI. A look at ascertaining the success of a train, test, split This article is a look at checking for a successful train, test, and split. Few tutorials discuss this step. The process of …
Tutorial: Data-deidentification of Text in the Electronic Medical Records
Author(s): Dr. Mandar Karhade, MD. PhD. Originally published on Towards AI. Data de-identification in Healthcare data is the biggest headache. Let's see how we can handle it The tutorial starts in the middle of the article — so if you want to …
Sexy Plotly Range Sliders: Prompting GPT-4 For Interactive Python Visuals
Author(s): John Loewen, PhD Originally published on Towards AI. A modular approach to Python plotly range slider code creationDall-E image: Impressionist interpretation of range slider in thick, rainbow colour Data visualization skills are an essential component of quality data analysis. For data …
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