Search Results for "sourceforge.net/projects/winpython/files/winpython_3.8/3.8.10.0/winpython64-3.8.10.0.7z"
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6 projects for "sourceforge.net/projects/winpython/files/winpython_3.8/3.8.10.0/winpython64-3.8.10.0.7z" with 2 filters applied:
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The top-rated AI recruiting platform for faster, smarter hiring.Humanly is an AI-first recruiting platform that helps talent teams hire in days, not months—without adding headcount. Our intuitive CRM pairs with powerful agentic AI to engage and screen every candidate instantly, surfacing top talent fast. Built on insights from over 4 million candidate interactions, Humanly delivers speed, structure, and consistency at scale—engaging 100% of interested candidates and driving pipeline growth through targeted outreach and smart re-engagement. We integrate seamlessly with all major ATSs to reduce manual work, improve data flow, and enhance recruiter efficiency and candidate experience. Independent audits ensure our AI remains fair and bias-free, so you can hire confidently.
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Construction Takeoff SoftwareStratosphere’s cutting edge cloud platform gives estimators unprecedented freedom to complete takeoffs from anywhere with next generation takeoff and markup tools.
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Zero to Mastery Deep Learning TensorFlow
All course materials for the Zero to Mastery Deep Learning with TF
...The material covers core machine learning workflows including regression, classification, computer vision, natural language processing, and time series forecasting, allowing users to build a well-rounded understanding of modern AI tasks. It also integrates milestone projects that simulate real-world scenarios, helping users translate abstract concepts into deployable solutions. -
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Open Model Zoo
Pre-trained Deep Learning models and demos
...It includes hundreds of models covering object detection, classification, segmentation, pose estimation, speech recognition, text-to-speech, and more, many of which are already converted into formats optimized for inference on CPUs, GPUs, VPUs, and other accelerators supported by OpenVINO. In addition to model files, Open Model Zoo provides demo applications that show realistic usage patterns and help developers quickly prototype and understand inference pipelines in C++, Python, or via the OpenCV Graph API. Tools in the repository also help automate model downloads and other tasks, making it easier to incorporate these models into production systems or custom solutions. -
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Deep Learning Models
A collection of various deep learning architectures, models, and tips
...Examples span fundamental architectures—MLPs, CNNs, RNN/Transformers—and practical tasks like image classification or text modeling. Reproducible training scripts and configuration files make it straightforward to rerun experiments or adapt them to your own datasets. The repo often pairs implementations with notes on design choices and trade-offs, turning it into both a toolbox and a learning resource. It’s suitable for students, researchers prototyping ideas, and practitioners who want clean baselines before adding complexity. -
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Deeplearning.ai
Study notes, summaries, and auxiliary materials for deep learning
...By organizing the content as “books” or structured notes, it gives students a consistent reference to revisit as models and tooling evolve. Many learners use it to supplement course videos, reinforcing concepts before implementing assignments or projects. As a consolidated guide, it reduces context-switching and helps build a durable mental model of deep learning fundamentals. -
Respond 100x faster, more accurately, and improve your documentationSlash response times for questionnaires, audits, and RFPs by up to 90%. OptiValue.ai automates the heavy lifting, freeing your team to focus on strategic priorities with intuitive tools for seamless review and validation.
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Learn_Deep_Learning_in_6_Weeks
This is the Curriculum for "Learn Deep Learning in 6 Weeks"
Learn_Deep_Learning_in_6_Weeks compresses an introductory deep learning curriculum into six weeks of structured learning and practice. It begins with neural network fundamentals and moves through convolutional and recurrent architectures, optimization strategies, regularization, and transfer learning. The materials emphasize code-first understanding: building small models, training them on accessible datasets, and analyzing their behavior. Each week culminates in a tangible outcome—such as a... -
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MatlabFunc
Matlab codes for feature learning
...These functions cover areas such as matrix operations, optimization, data processing, and visualization, making them broadly applicable across different research domains. The project is intended to provide reusable and adaptable MATLAB code that can save time for researchers and students working on experimental or applied projects. By consolidating these tools in one place, MatlabFunc serves as a practical reference and toolkit for both academic and engineering purposes. Contributions and improvements from the community are encouraged, allowing the repository to grow into a richer resource over time.
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