Snack Slack Bot
Donut Slack Bot
Macarons
Catchup Rocks
GreetBot
Donut.ai
Micronet.social
Coffee Chat Slack
NumPy
Pandas
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
WEKA
Virtual snack breaks that build authentic team relationships Have spontaneous, time-restricted video conversations with ice-breakers.
Snack introduces people in your Slack to have short video conversations with ice-breakers. Snack meetings have the same kind of joyful feeling that you experience when you meet and chat with someone new in the office hallway, by the water cooler or during a lunch break. We are your virtual office snack club.
Snack is 100% opt-in. Your team only gets notifications when they choose to participate by joining #snack-club channel. Learn how Snack works →
300+ teams are already using Snack, including Dell, IBM, Globant, University of California, AKQA, and Giphy.
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Slack is the best tool I found to stay connected with my team across the globe. I've tried Donut too and Slack is 10x better in terms of speed, features and UI. This app has no competition.
I've tested Snack in a dozen Slack teams. It is the fastest way to make friends in a Slack organization.
Based on our record, NumPy seems to be a lot more popular than Snack Slack Bot. While we know about 112 links to NumPy, we've tracked only 1 mention of Snack Slack Bot. 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.
I've launched Snack at the beginning of the year. I had a big vision of how a simple Slack bot will grow to a remote culture building software handling everything from onboarding to insurance. It slowly grew to over 2000 companies trying Snack water cooler feature to spice things up. However, otherwise project stagnated since I simply do not have time to release new features or even answer support tickets. Source: about 3 years ago
How to Accomplish: Develop a script that iterates over the image database, preprocesses each image according to the model's requirements (e.g., resizing, normalization), and feeds them into the model for prediction. Ensure the script can handle large datasets efficiently by implementing batch processing. Use libraries like NumPy or Pandas for data management and TensorFlow or PyTorch for model inference. Include... - Source: dev.to / 12 days ago
NumPy: This library is fundamental for handling arrays and matrices, such as for operations that involve image data. NumPy is used to manipulate image data and perform calculations for image transformations and mask operations. - Source: dev.to / 13 days ago
NumPy - The fundamental package for scientific computing with Python. NumPy Documentation - Official documentation. - Source: dev.to / 18 days ago
This guide covers the basics of NumPy, and there's much more to explore. Visit numpy.org for more information and examples. - Source: dev.to / 20 days ago
Below is an example of a code cell. We'll visualize some simple data using two popular packages in Python. We'll use NumPy to create some random data, and Matplotlib to visualize it. - Source: dev.to / 10 months ago
Donut Slack Bot - Get matched with a new coffee buddy each week in Slack
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Macarons - Macarons is your virtual watercooler for casual conversations with colleagues you rarely meet on the hallway.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Catchup Rocks - Virtual coffee / watercooler chats for Slack.
OpenCV - OpenCV is the world's biggest computer vision library