Analytics Bridge
Jupyter
Hue
Thonny
Hex
iPython
Apache Zeppelin
JASP
PyTorch
TensorFlow
Scikit-learn
Keras
OpenCV
NumPy
CUDA Toolkit
Pandas
Analytics Bridge is a collaborative data analytics platform where teams can raise data requests, share SQL queries, and document insights. With Ask Anaya, an AI-powered data analyst, users get instant answers, query suggestions, and automated insights. It streamlines analysis, enhances collaboration, and ensures seamless data-driven decision-making.
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Analytics Bridge is designed for data-driven teams and professionals who need a seamless way to collaborate on analytics, automate insights, and document findings efficiently.
Whether you’re a startup, enterprise, or data-driven organization, Analytics Bridge simplifies analytics, enhances collaboration, and ensures insights are always documented.
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Analytics Bridge stands out by combining AI-powered insights, seamless collaboration, and real-time database connectivity—all in one platform.
With Ask Anaya leading the way, Analytics Bridge isn’t just another BI tool—it’s a smarter, faster, and more collaborative way to analyze data. 🚀
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Based on our record, PyTorch seems to be more popular. It has been mentiond 135 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.
Machine learning (ML) teaches computers to learn from data, like predicting user clicks. Start with simple models like regression (predicting numbers) and clustering (grouping data). Deep learning uses neural networks for complex tasks, like image recognition in a Vue.js gallery. Tools like Scikit-learn and PyTorch make it easier. - Source: dev.to / about 2 months ago
Explicit CUDA/GPU version: on https://pytorch.org, select your OS and desired CUDA version, and then modify the generated command to include your torch version. - Source: dev.to / 3 months ago
To aspiring innovators: Dive into open-source frameworks like OpenCV or PyTorch, experiment with custom object detection models, or contribute to projects tackling bias mitigation in training datasets. Computer vision isn’t just a tool, it’s a bridge between the physical and digital worlds, inviting collaborative solutions to global challenges. The next frontier? Systems that don’t just interpret visuals, but... - Source: dev.to / 5 months ago
With the quick emergence of new frameworks, libraries, and tools, the area of artificial intelligence is always changing. Programming language selection. We're not only discussing current trends; we're also anticipating what AI will require in 2025 and beyond. - Source: dev.to / 5 months ago
Next, we define a training loop that uses our prepared data and optimizes the weights of the model. Here's an example using PyTorch:. - Source: dev.to / 6 months ago
Jupyter - Project Jupyter exists to develop open-source software, open-standards, and services for interactive computing across dozens of programming languages. Ready to get started? Try it in your browser Install the Notebook.
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.
Hue - Unlimited design for startups to enterprises
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Thonny - Python IDE for beginners
Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.
