Learn how to build apps and showcase your skills with large language models (LLMs). Get started today! — One common piece of advice I often hear for job applicants is to have a portfolio showcasing your work. This doesn't only apply to artists or models but also to software developers and data scientists. A portfolio of your projects acts as public evidence of your skills. This public evidence…

Fine-tuning pre-trained Deep Learning models in Python — This practical tutorial shows you how to classify images using a pre-trained Deep Learning model with the PyTorch framework. The difference between this beginner-friendly image classification tutorial to others is that we are not building and training the Deep neural network from scratch. In practice, only a few people train…

How LLMs are changing the way we build AI-powered products and the landscape of MLOps — This article was originally published on the Weights & Biases’ blog “Fully Connected” on April 21st, 2023. It feels like the release of OpenAI’s ChatGPT has opened Pandora’s box of large language models (LLMs) in production. Not only does your neighbor now bother you with small talk about Artificial Intelligence…

A LangChain tutorial to build anything with large language models in Python — Since the release of ChatGPT, large language models (LLMs) have gained a lot of popularity. Although you probably don’t have enough money and computational resources to train an LLM from scratch in your basement, you can still use pre-trained LLMs to build something cool, such as: Personal assistants that can…

Data augmentation techniques for Computer Vision implemented in Python — It’s almost guaranteed that applying data augmentations will improve the performance of your neural network. Augmentations are a regularization technique that artificially expands your training data and helps your Deep Learning model generalize better. Thus, image augmentations can improve the model performance. Image augmentations can improve the model performance

How to check if a time series is stationary and what you can do if it is non-stationary in Python — The future is easier to model when it is similar to the present [3]. Stationarity describes the concept that the statistical features of a time series do not change over time. Thus, some time series forecasting models, such as autoregressive models, rely on the stationarity of the time series. In…

A complete guide to saving and loading checkpoints and entire Deep Learning models in PyTorch and TensorFlow/Keras — Training a neural network often takes a lot of time and computational resources. It would be a shame to lose a model after putting in that time and computation. That’s why you should be able to save and load a Deep Learning model in its different stages (during training or…

Fine-tuning image models to tackle domain shift and class imbalance with PyTorch and torchaudio in audio data — Welcome to another edition of “The Kaggle Blueprints”, where we will analyze Kaggle competitions’ winning solutions for lessons we can apply to our own data science projects. This edition will review the techniques and approaches from the “BirdCLEF 2022” competition, which ended in May 2022.

How to augment audio in waveform (time domain) and as spectrograms (frequency domain) with librosa, numpy, and PyTorch — Deep Learning models are data-hungry. If you don’t have a sufficient amount of data, generating synthetic data from the available dataset can help improve the generalization capabilities of your Deep Learning model. While you might already be familiar with data augmentation techniques for images (e.g., flipping an image horizontally), data…