Aquarium
Scale Nucleus
PerceptiLabs
ML Image Classifier
Google Cloud TPUs
Roboflow Universe
Prodigy
mlblocks
Pandas
NumPy
Scikit-learn
OpenCV
Dataiku
Exploratory
htm.java
WEKA
Aquarium PandasPandas is particularly recommended for data scientists, analysts, and engineers who need to perform data cleaning, transformation, and analysis as part of their work. It is also suitable for academics and researchers dealing with data in various formats and needing powerful tools for their data-driven research.
Based on our record, Pandas seems to be a lot more popular than Aquarium. While we know about 219 links to Pandas, we've tracked only 2 mentions of Aquarium. 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.
Aquarium (https://aquariumlearning.com/) | Remote Only (North American Timezones) | Full Time Aquarium is an ML data management system that helps ML teams improve their models by improving their datasets. Aquarium uncovers problems in your dataset, then helps you edit or add data to fix these problems and optimize your model performance. We are looking for our first Product Manager and are also hiring for... - Source: Hacker News / over 3 years ago
#ML is maturing and teams are less concerned about having enough #data, but rather having the right data. ML data management tooling helps improve ML models by improving datasets. Check out our piece below that discusses trends in the space and startups like aquariumlearning.com, Tryunbox.ai, Lightly.ai, Scale, and Labelbox. https://medium.com/memory-leak/ml-data-management-a-primer-a635a5eac858. Source: almost 4 years ago
Libraries for data science and deep learning that are always changing. - Source: dev.to / about 1 month ago
# Read the content of nda.txt Try: Import os, types Import pandas as pd From botocore.client import Config Import ibm_boto3 Def __iter__(self): return 0 # @hidden_cell # The following code accesses a file in your IBM Cloud Object Storage. It includes your credentials. # You might want to remove those credentials before you share the notebook. Cos_client = ibm_boto3.client(service_name='s3', ... - Source: dev.to / about 2 months ago
As with any web scraping or data processing project, I had to write a fair amount of code to clean this up and shape it into a format I needed for further analysis. I used a combination of Pandas and regular expressions to clean it up (full code here). - Source: dev.to / about 2 months ago
Python’s Growth in Data Work and AI: Python continues to lead because of its easy-to-read style and the huge number of libraries available for tasks from data work to artificial intelligence. Tools like TensorFlow and PyTorch make it a must-have. Whether you’re experienced or just starting, Python’s clear style makes it a good choice for diving into machine learning. Actionable Tip: If you’re new to Python,... - Source: dev.to / 4 months ago
This tutorial provides a concise and foundational guide to exploring a dataset, specifically the Sample SuperStore dataset. This dataset, which appears to originate from a fictional e-commerce or online marketplace company's annual sales data, serves as an excellent example for learning and how to work with real-world data. The dataset includes a variety of data types, which demonstrate the full range of... - Source: dev.to / 9 months ago
Scale Nucleus - The mission control for your ML data
NumPy - NumPy is the fundamental package for scientific computing with Python
PerceptiLabs - A tool to build your machine learning model at warp speed.
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
ML Image Classifier - Quickly train custom machine learning models in your browser
OpenCV - OpenCV is the world's biggest computer vision library
