Colaboratory— Free web-based Python notebook environment with Nvidia Tesla K80 GPU. Collect2— Create an API endpoint to test, automate, and connect webhooks. The free plan allows for two datasets, 2000 records, one forwarder, and one alert. CometML - The MLOps platform for experiment trac...
VisiData - (Repo, Home, Fund, PyPI, Docs) Interactive multitool for exploring, analyzing, and converting datasets in the terminal. (linux, mac, tui) Vorta - (Repo, Home) GUI backup client built on top of BorgBackup. (linux, mac) wttr.in - (Repo, Home) Weather forecast service that ...
Andrew Collette
Spark NLP: Built on top of Apache Spark, it’s designed for distributed processing and handling large datasets at scale. This makes it especially suitable for big data processing tasks that need to run on a cluster. spaCy: Designed for processing data on a single machine and it’s not nati...
John Stone, senior research programmer at the Beckman Institute at the University of Illinois, Urbana-Champaign, discusses how CUDA and GPUs are used to process large datasets to visualize and simulate high-resolution atomic structures. Watch Video ...
Cassandra offers a great solution for managing vast datasets. I tested this tool extensively, and I particularly liked how it allows data replication across several datacenters, which is required for failover strategies. It is a top choice for businesses dealing with distributed networks. Cassandra ...
Free PDF | Python for Data Analysis: Data Wrangling with pandas, NumPy, and Jupyter 3rd Edition Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.10 and pandas 1.4, the third edition of this hands-on guide is packed with...
The ISLP Python Package The book uses datasets sourced from publicly available repositories such as the UCI Machine Learning repository and other similar resources. Some examples include datasets on bike sharing, credit card default, fund management, and crime rates. ...
Dr. Robert Kübler August 20, 2024 13 min read Hands-on Time Series Anomaly Detection using Autoencoders, with Python Data Science Here’s how to use Autoencoders to detect signals with anomalies in a few lines of… Piero Paialunga ...
使用python实现CenterNet #!/usr/bin/env pythonimportosimportjsonimporttorchimportpprintimportargparseimportimportlibimportnumpyasnpimportmatplotlibmatplotlib.use("Agg")fromconfigimportsystem_configsfromnnet.py_factoryimportNetworkFactoryfromdb.datasetsimportdatasetstorch.backends.cudnn.benchmark=Falsedefparse_args()...