BytesView
Medallia
MeaningCloud
Talkwalker
Amazon Comprehend
Currents by Parse.ly
Replika
Newsdata.io
NumPy
Pandas
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
Figure Eight
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Bytesview made it easier for us to bring our customers to the forefront by introducing new customer-focused services based on their feedback.
The team is extremely friendly and helped us find innovative solutions to our problem
I've been using Bytesview for a few weeks now and I really like it! It is straightforward and easy to analyze the feedback data collected and gain a better understanding of our customer base.
The tool's data processing was simple, and the results were accurate.
BytesView's in-depth data analysis enabled me to extract personalized insights for my research project. They collected text data from various websites, translated user sentiment, and extracted various keywords for me, which was incredibly helpful during my research.
Moreover, their team was extremely helpful to me throughout the process.
Based on our record, NumPy seems to be a lot more popular than BytesView. While we know about 122 links to NumPy, we've tracked only 2 mentions of BytesView. 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.
It is also not a task that a team of analysts, no matter how large or dedicated, could reasonably be expected to perform, at least not without outside assistance. Even for organizations that are in the business of selling competitive intelligence platforms (many of which are Bytesview customers), this is not a viable option. Source: over 4 years ago
News monitoring services, powered by a sentiment analyzer, and News API are more necessary than ever when every action of a company, its employees, brand ambassadors, or even the organizations with which it is associated is subject to scrutiny, which in turn undermines the financial stability of the company. Source: over 4 years ago
Unmatched integration with ML/AI ecosystems through NumPy, TensorFlow, and PyTorch. - Source: dev.to / 9 months ago
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโฆ. - Source: dev.to / 10 months ago
AI starts with math and coding. You donโt need a PhDโjust high school math like algebra and some geometry. Linear algebra (think matrices) and calculus (like slopes) help understand how AI models work. Python is the main language for AI, thanks to tools like TensorFlow and NumPy. If you know JavaScript from Vue.js, Pythonโs syntax is straightforward. - Source: dev.to / 12 months ago
The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / over 1 year ago
This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / almost 2 years ago
Medallia - Medallia enables companies to capture customer feedback, understand it in real-time, and take action to improve the customer experience (CX).
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
MeaningCloud - Extract meaning from unstructured text and turn it into actionable insights.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Talkwalker - Talkwalker Consumer Intelligence Platform: built for speed of insight, ease of use, and data democratization
OpenCV - OpenCV is the world's biggest computer vision library
