Based on our record, Jupyter should be more popular than PyTorch. It has been mentiond 206 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Interesting, I would have guessed you had used something jupyter-like: https://jupyter.org/ https://explorabl.es/all/. - Source: Hacker News / about 1 month ago
JupyterLab: JupyterLab is an interactive development environment that allows you to create and share documents containing live code, equations, visualizations, and narrative text. It's particularly well-suited for data science and research-oriented projects. - Source: dev.to / about 2 months ago
Jupyter Lab web-based interactive development environment. - Source: dev.to / 2 months ago
Choosing IDE: Selecting a suitable Integrated Development Environment (IDE) is crucial for efficient coding. Consider popular options such as PyCharm, Visual Studio Code, or Jupyter Notebook. Install your preferred IDE and ensure it's configured to work with Python. - Source: dev.to / about 2 months ago
Jupyter Notebooks is very popular among data people specially Python users. So, I tried to find a way to run the Groovy kernel inside a Jupyter Notebook, and to my surprise, I found a way, BeakerX! - Source: dev.to / 3 months ago
Hi everyone! I’m devloker, and today I’m excited to share a project I’ve been working on: a digit recognition system implemented using pure math functions in Python. This project aims to help beginners grasp the mathematics behind AI and digit recognition without relying on high-level libraries like TensorFlow or PyTorch. You can find the complete code on my GitHub repository. - Source: dev.to / 1 day ago
PyTorch - An open source machine learning framework. PyTorch Tutorials - Tutorials and documentation. - Source: dev.to / 8 days ago
In this guide, we provided a comprehensive, step-by-step explanation of how to implement a simple GPT (Generative Pre-trained Transformer) model using PyTorch. We walked through the process of creating a custom dataset, building the GPT model, training it, and generating text. This hands-on implementation demonstrates the fundamental concepts behind the GPT architecture and serves as a foundation for more complex... - Source: dev.to / 16 days ago
PyTorch is a powerful and flexible deep learning framework that offers a rich set of features for building and training neural networks. - Source: dev.to / 24 days ago
Oddly enough, sometimes, the best way to learn is by putting forth incorrect opinions or questions. Recently, while wrestling with AI project complexities, I pondered aloud whether all Docker images with AI models would inevitably be bulky due to PyTorch dependencies. To my surprise, this sparked many helpful responses, offering insights into optimizing image sizes. Being willing to be wrong opens up avenues for... - Source: dev.to / 17 days ago
Looker - Looker makes it easy for analysts to create and curate custom data experiences—so everyone in the business can explore the data that matters to them, in the context that makes it truly meaningful.
TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.
Google BigQuery - A fully managed data warehouse for large-scale data analytics.
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
Databricks - Databricks provides a Unified Analytics Platform that accelerates innovation by unifying data science, engineering and business.What is Apache Spark?
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.