PicPurify
Sightengine
Cloudimage
imgix
Monthly
IMG.LY
Publitio
Gumlet
Scikit-learn
Pandas
OpenCV
NumPy
Dataiku
WEKA
htm.java
Exploratory
The core algorithm behind PicPurify is built based on the most advanced deep learning technology. This algorithm is inspired by the human visual system, and is continuously learning how to identify specific contents in an image by scanning millions of them.
Picpurify use the most advanced deep-learning algorithms to deliver an unprecedented accuracy on the moderation of harmful content. That make us expert in computer vision problematics. Our company has trained and then fine-tuned several convolutional neural networks to perform various tasks of classification and detection over images in the context of filtering specific contents for companies.
We fully managed all the steps related to the creation of a deep learning model, starting from the data collection/annotation to the training and optimization of the algorithms. It allow us to provide tailor-made models to companies.
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Based on our record, Scikit-learn seems to be more popular. It has been mentiond 31 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.
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 / 3 months ago
Scikit-learn (optional): Useful for additional training or evaluation tasks. - Source: dev.to / 5 months ago
How to Accomplish: Utilize data splitting tools in libraries like Scikit-learn to partition your dataset. Make sure the split mirrors the real-world distribution of your data to avoid biased evaluations. - Source: dev.to / 11 months ago
Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / about 1 year ago
Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / almost 2 years ago
Sightengine - Effortless moderation of user-submitted photos. Instantly detect nudity and adult content with our easy-to-use API, for a fraction of the cost of human moderation
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Cloudimage - Cloudimage.io is the easiest way to resize, store, and deliver your images to your customers through a rocket fast CDN.
OpenCV - OpenCV is the world's biggest computer vision library
imgix - Real-time Image Processing. Resize, crop, and process images on the fly, simply by changing their URLs.
NumPy - NumPy is the fundamental package for scientific computing with Python