Dcipher Analytics can save insight professionals valuable time by automating their tedious work so they can focus on what the insights mean for their organization and how they can take the best course of action. The platform accelerates the time-to-insight, model training, and automation of workflows for all analysts and insight professionals.
What makes us unique?
Dcipher Analytics is a unique solution for automating insight workflows. It provides all the data sources, automated workflows, algorithms, and AI tools you need in one place. Interact with data through an intuitive visual interface to prep, explore, enrich, and build models faster than ever before—all without the need to code.
Code-Free AI: Placing the power of state-of-the-art algorithms and models in the hands of analysts and insight professionals, making the world’s most powerful AI models easy to use through simple drag-and-drop.
Flexible End-to-End Solutions: Making it easy to automate the process of extracting insights from unstructured text according to your needs. Select all the sources, methods, and models you need in a unified and interoperable platform.
Enterprise-grade technology at scale, with speed: Achieving quick time-to-insight at the scale of your needs, whether you want to analyze a single report or millions of news articles. Leverage distributed and fully parallelized computing in the cloud to optimize for datasets of all sizes.
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Based on our record, Pandas seems to be more popular. It has been mentiond 201 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.
How to Accomplish: Use statistical analysis tools and libraries (e.g., Pandas for tabular data) to calculate and visualize these characteristics. For image datasets, custom scripts to analyze object sizes or mask distributions can be useful. Tools like OpenCV can assist in analyzing image properties, while libraries like Pandas and NumPy are excellent for tabular and numerical analysis. To address class... - Source: dev.to / 12 days ago
Pandas - A powerful data analysis and manipulation library for Python. Pandas Documentation - Official documentation. - Source: dev.to / 18 days ago
It's also possible for you to give a package an alias by using the as keyword. For instance, you could use the pandas package as pd like this:. - Source: dev.to / about 2 months ago
Python is a natural fit for serverless development. It boasts a vast array of libraries, including Powertools for AWS and robust libraries for data engineers. Its versatility and excellent developer experience make it a top choice for serverless projects, offering a seamless and enjoyable development experience. - Source: dev.to / 2 months ago
In data analysis, managing the structure and layout of data before analyzing them is crucial. Python offers versatile tools to manipulate data, including the often-used Pandas reset_index() method. - Source: dev.to / 2 months ago
NumPy - NumPy is the fundamental package for scientific computing with Python
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OpenCV - OpenCV is the world's biggest computer vision library
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Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
QATTS - A next-gen, end to end Test Automation Software built for Enterprise.