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Examples Alternatives
Similar projects and alternatives to examples
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Pytorch
Tensors and Dynamic neural networks in Python with strong GPU acceleration
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Pandas
Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
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SonarQube
Static code analysis for 29 languages.. Your projects are multi-language. So is SonarQube analysis. Find Bugs, Vulnerabilities, Security Hotspots, and Code Smells so you can release quality code every time. Get started analyzing your projects today for free.
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InfluxDB
Build time-series-based applications quickly and at scale.. InfluxDB is the Time Series Platform where developers build real-time applications for analytics, IoT and cloud-native services. Easy to start, it is available in the cloud or on-premises.
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Apache Spark
Apache Spark - A unified analytics engine for large-scale data processing
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awesome-teachable-machine
Useful resources for creating projects with Teachable Machine models + curated list of already built Awesome Apps!
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face-api.js
JavaScript API for face detection and face recognition in the browser and nodejs with tensorflow.js
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fastapi
FastAPI framework, high performance, easy to learn, fast to code, ready for production
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
NOTE:
The number of mentions on this list indicates mentions on common posts plus user suggested alternatives.
Hence, a higher number means a better examples alternative or higher similarity.
examples reviews and mentions
Posts with mentions or reviews of examples.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2023-01-31.
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#01 Benchmark of four JIT Backends
The participants are also shown in the cover image, which are : Numba, JAX, Tensorflow, Triton.
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What are the best Python libraries to learn for beginners?
TensorFlow and PyTorch: Deep learning library
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Best Websites For Coders
TensorFlow : An open-source software library for Machine Intelligence
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DataOps 101: An Introduction to the Essential Approach of Data Management Operations and Observability
DataOps is a collaborative effort within an organization, with many different teams of people working together to ensure that DataOps functions properly and delivers data value [3]. So, before the data is delivered to end users, it is subjected to a number of treatments and refinements from multiple teams. Data scientists first use their data science techniques, such as machine learning and deep learning to build models using software stacks such as Python or R and tools such as Spark or Tensorflow, among others, and the models are then transferred to data engineers, who collect and manage the data used to train and evaluate these models, while data developers and data architects create complete applications that include the models. The data governance team then implements data access controls for training and benchmarking purposes, while the operations team ( "Ops") is in charge of putting everything together and making it available to end users.
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DO YOU YAML?
The M2 MacBook gave me some challenges when trying to work with TensorFlow and Keras due to some fancy chip architecture which you can read about here: TensorFlow with GPU support on Apple Silicon Mac with Homebrew and without Conda / Miniforge
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Realtime object detection android app
It looks like the TFlite Object detector from their training site.
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IT a trh práce
Python se pouziva vsude a nema specializaci. Asi jedina oblast kde vylozene vynika je Data Science a AI.
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Инструменты Python. Библиотеки для анализа данных
- tensorflow (https://www.tensorflow.org);
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Markdown, Asciidoc, or reStructuredText – a tale of docs-as-code
It's in JSON at least by default. Here's an example: https://github.com/tensorflow/examples/blob/master/courses/u...
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Where to start with AI? I know, asked a million times
If you want to get your hands dirty as fast as possible, skip the first 3 resources, head to https://www.tensorflow.org/ and start coding. https://www.tensorflow.org/resources/learn-ml here you can find some practical intro to ml, and you can also do some tutorials on the learn tab. If you lose the thread or something doesn’t make sense, then you can review specific topics in the ml course or the deep learning book to get some theoretical understanding.
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A note from our sponsor - #<SponsorshipServiceOld:0x00007fea594db688>
www.saashub.com | 31 Jan 2023
Stats
Basic examples repo stats
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8.5
1 day ago
tensorflow/examples is an open source project licensed under Apache License 2.0 which is an OSI approved license.
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