Search Results for "deep" - Page 2
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Showing 38 open source projects for "deep"
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Stop Cyber Threats with VM-Series Next-Gen Firewall on AzureGain integrated visibility across all traffic in a single pass. Deploy Palo Alto Networks VM-Series to determine application identity and content while automating security policy updates via rich APIs.
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Build Agents and Models on One PlatformGemini Enterprise Agent Platform is Google Cloud's comprehensive platform for developers to build, scale, govern, and optimize agents and models. Choose from Google's most advanced models and third-party models like Anthropic's Claude Model Family.
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Deep Learning course
Slides and Jupyter notebooks for the Deep Learning lectures
Slides and Jupyter notebooks for the Deep Learning lectures at Master Year 2 Data Science from Institut Polytechnique de Paris. This course is being taught at as part of Master Year 2 Data Science IP-Paris. Note: press "P" to display the presenter's notes that include some comments and additional references. This lecture is built and maintained by Olivier Grisel and Charles Ollion. -
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ReinforcementLearningAnIntroduction.jl
Julia code for the book Reinforcement Learning An Introduction
...One of our main goals is to help users understand the basic concepts of reinforcement learning from an engineer's perspective. Once you have grasped how different components are organized, you're ready to explore a wide variety of modern deep reinforcement learning algorithms in ReinforcementLearningZoo.jl. -
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Amazon SageMaker Examples
Jupyter notebooks that demonstrate how to build models using SageMaker
...If you’re new to SageMaker we recommend starting with more feature-rich SageMaker Studio. It uses the familiar JupyterLab interface and has seamless integration with a variety of deep learning and data science environments and scalable compute resources for training, inference, and other ML operations. Studio offers teams and companies easy on-boarding for their team members, freeing them up from complex systems admin and security processes. Administrators control data access and resource provisioning for their users. ... -
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TensorWatch
Debugging, monitoring and visualization for Python Machine Learning
TensorWatch is an open source debugging and visualization platform created by Microsoft Research to support machine learning, deep learning, and reinforcement learning workflows. It enables developers to observe training behavior in real time through interactive visualizations, primarily within Jupyter Notebook environments. The tool treats most data interactions as streams, allowing flexible routing, storage, and visualization of metrics generated during model training. -
AI Agents That Actually Do the WorkClickUp's Super Agents run 24/7 inside your workspace: triaging bugs, drafting content, updating statuses, and routing tasks without being told twice. Connect them to 500+ tools and let them execute, not just suggest. Build custom agents in minutes that understand your workflows and act on them autonomously.
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Deep Learning with PyTorch
Latest techniques in deep learning and representation learning
This course concerns the latest techniques in deep learning and representation learning, focusing on supervised and unsupervised deep learning, embedding methods, metric learning, convolutional and recurrent nets, with applications to computer vision, natural language understanding, and speech recognition. The prerequisites include DS-GA 1001 Intro to Data Science or a graduate-level machine learning course. -
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CapAnalysis
PCAP from another point of view
CapAnalysis is a web visual tool for information security specialists, system administrators and everyone who needs to analyze large amounts of captured network traffic. Analyze TCP and UDP streams Support multible datasets Perform deep packet inspection Support filtering capability Source Code: https://github.com/xplico/CapAnalysis -
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Merlin.jl
Deep Learning for Julia
Merlin is a deep learning framework written in Julia. It aims to provide a fast, flexible and compact deep learning library for machine learning. Merlin is tested against Julia 1.0 on Linux, OS X, and Windows (x64). -
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Seldon Server
Machine learning platform and recommendation engine on Kubernetes
...Seldon Server is a machine learning platform that helps your data science team deploy models into production. It provides an open-source data science stack that runs within a Kubernetes Cluster. You can use Seldon to deploy machine learning and deep learning models into production on-premise or in the cloud (e.g. GCP, AWS, Azure). -
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DeepLearningProject
An in-depth machine learning tutorial
This tutorial tries to do what most Most Machine Learning tutorials available online do not. It is not a 30 minute tutorial that teaches you how to "Train your own neural network" or "Learn deep learning in under 30 minutes". It's a full pipeline which you would need to do if you actually work with machine learning - introducing you to all the parts, and all the implementation decisions and details that need to be made. The dataset is not one of the standard sets like MNIST or CIFAR, you will make you very own dataset. Then you will go through a couple conventional machine learning algorithms, before finally getting to deep learning! ... -
Stop vibe-debugging.AppSignal's MCP server hands Claude, Cursor, or Zed your real errors, traces, and the deploy that shipped them. AI writes the fix; you review the diff.
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json4sapnw
Another JSON extension for SAP ABAP
...It comes in the customer exchange namespace /CEX/ and has to be installed as an SAP transport request. The addon supports object oriented JSON methods to process deep structured JSON data. Building JSON data from SAP data objects and parsing JSON data back to SAP data objects are supported. See the WIKI for some examples. Thanks to the SAP community and especially to Rüdiger Plantiko for the basic work (http://ruediger-plantiko.blogspot.de/2010/12/ein-json-parser-in-abap.html). Enjoy! ... -
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HomSI
Homozygous Stretch Identifier from next-generation sequencing data
...Recently, the advent of next generation sequencing enables the concurrent identification of homozygous regions and the detection of mutations relevant for diagnosis, using data from a single sequencing experiment. In this respect, we have developed a novel tool that identifies homozygous regions using deep sequence data. Using *.vcf files as an input file, our program identifies the majo -
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BriPy
A BRIC-seq data analysis package written in Python.
-What is BRIC-seq? BRIC-seq, short for 5'-bromo-uridine (BrU) immunoprecipitation chase-deep sequencing analysis, is a novel method in Next Generation Sequencing (NGS) to determine the RNA stability of each transcript. It employs metabolic labeling by BrU of newly synthesized RNAs to chase chronological decreases of BrU-labeled RNA (Pulse-chase labeling), followed by immunoprecipitation with antibody for BrU, construction of cRNA library for High-throughput sequencing and computational data analysis. ... -
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Mandelbrot Viewer
View the Mandelbrot set easily at high zooms
A simple Java application to view the Mandelbrot set at almost any zoom and resolution and save images of it to a file. Features: -high precision for deep zooms -background threads to prevent GUI freezing -adjustable color scheme -easy point-and-zoom fractal browsing
