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Help: Slow performance with windows 10 compared to Ubuntu 20.04 with TF2.7
1 project | reddit.com/r/tensorflow | 24 May 2022
Can anyone offer up an explanation for why there is a performance difference, and if possible, what could be done to fix it. I'm using the installation guidelines found on tensorflow.org and installing tf2.7 through pip using an anaconda3 env.
A smart way to print :)
6 projects | reddit.com/r/Python | 22 May 2022
1 project | news.ycombinator.com | 18 May 2022
How could I use batch normalization in TensorFlow?
1 project | reddit.com/r/codehunter | 17 Apr 2022
I would like to use batch normalization in TensorFlow. I found the related C++ source code in core/ops/nn_ops.cc. However, I did not find it documented on tensorflow.org.
[P] Neural Network for Image Classification
3 projects | reddit.com/r/SubSimulatorGPT2 | 16 Apr 2022
When I'm on a project & cloning a repo, which branch should I clone?
2 projects | reddit.com/r/learnprogramming | 13 Apr 2022
If data science uses a lot of computational power, then why is python the most used programming language?
6 projects | reddit.com/r/learnmachinelearning | 13 Apr 2022
For reference: In Tensorflow and JAX, for example, the tensor gets compiled to the intermediate XLA format (https://www.tensorflow.org/xla), then passed to the XLA complier (https://github.com/tensorflow/tensorflow/tree/master/tensorflow/compiler/xla/service) or the new TFRT runtime (https://github.com/tensorflow/runtime/blob/master/documents/tfrt_host_runtime_design.md), or some more esoteric hardware (https://github.com/pytorch/glow).
FFmpeg for Super Resolution on Ubuntu 20.04 : libtensorflow_framework Relink Error
1 project | reddit.com/r/linuxquestions | 10 Apr 2022
Looks like it's tensorflow-related, however I have verified that tensorflow is working properly on my system. I could find nothing on Google, there's just one thread discussing exactly the same error (here), however there is still no solution as well. I am aware the error is not symlink related, but just in case this information is needed : (or see in gist)
[Question] What are the best tutorials and resources for implementing NLP techniques on TensorFlow?
3 projects | reddit.com/r/SubSimulatorGPT2 | 7 Apr 2022
I don't have much experience with TensorFlow, but I'd recommend starting with TensorFlow.org3 projects | reddit.com/r/SubSimulatorGPT2 | 7 Apr 2022
I have looked at this TensorFlow website and TensorFlow.org and some of the examples are written by others, and it seems that I am stuck in RNNs. What is the best way to install TensorFlow, to follow the documentation and learn the methods in RNNs in Python? Is there a good tutorial/resource?
[D] PyTorch processes taking up tons of GPU memory - any way to reduce this?
1 project | reddit.com/r/MachineLearning | 25 May 2022
Maybe related: https://github.com/pytorch/pytorch/issues/12873
SWAHILI TEXT CLASSIFICATION USING TRANSFORMERS
4 projects | dev.to | 24 May 2022
Let's dive into the main topic of this article, we are going to train a transformer model for Swahili news classification, Since transformers are large to make the task simple we need to select a wrapper to work with, if you are good with PyTorch you can use PyTorch Lightning a wrapper for high-performance AI research, to wrap the transformers but today lets go with ktrain from Tensorflow Python Library.
AUDIO CLASSIFICATION USING DEEP LEARNING
3 projects | dev.to | 20 May 2022
The second option is to train your own model using machine learning frameworks like Tensorflow and Pytorch.
[D] My experience with running PyTorch on the M1 GPU
4 projects | reddit.com/r/MachineLearning | 19 May 2022
AUTOMATED SPEECH RECOGNITION APPROACHES AND CHALLENGES
2 projects | dev.to | 19 May 2022
The goal of this approach is to replace the intermediate steps with one algorithm. The deep learning approach has achieved state-of-the-art results in speech transcription tasks and is replacing the traditional methods used in ASR. It is also simpler because there are fewer steps involved and does not require as much expertise. The implementation of this approach requires a knowledge understanding of deep learning tools such as PyTorch, Tensorflow, DeepSpeech, etc.
Accelerated PyTorch Training on M1 Mac
6 projects | news.ycombinator.com | 18 May 2022
> Is too limited? Too hard to interact with? Not worth the effort?
IIRC the only way to access ANE is through the Accelerate framework, and it seems to have pretty severe limitations.
Apple has developed a tensorflow plugin but i can't tell you if it uses ANE. Earlier this year they also published a job offer talking about accelerating PyTorch with BNNS and Accelerate. Apparently PyTorch already uses Accelerate and AMX (the matrix coprocessor).
So might indeed be that ANE is too limited and Accelerate never gets to use it.
sono abbastanza nuovo in ai e machine learning, non so da dove cominciare ma voglio concentrare i miei sforzi e studiare come creare modelli/e fake per la moda (ad esempio), che tipo di tecnologia/freamwork devi studiare?
2 projects | reddit.com/r/ItalyInformatica | 18 May 2022
Discrete Algebraic Ricatti Equation Solver
4 projects | reddit.com/r/ControlTheory | 10 May 2022
What is the requirement of something to be compatible with PyTorch? You can in fact ask them about this specifically, they are always a helpful bunch https://github.com/pytorch/pytorch
Introduction to PyTorch
7 projects | dev.to | 2 May 2022
PyTorch GitHub7 projects | dev.to | 2 May 2022
What is PyTorch
What are some alternatives?
PaddlePaddle - PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）
Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
Flux.jl - Relax! Flux is the ML library that doesn't make you tensor
scikit-learn - scikit-learn: machine learning in Python
LightGBM - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.
mediapipe - Cross-platform, customizable ML solutions for live and streaming media.
xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow
Keras - Deep Learning for humans
LightFM - A Python implementation of LightFM, a hybrid recommendation algorithm.
MLflow - Open source platform for the machine learning lifecycle
Apache Spark - Apache Spark - A unified analytics engine for large-scale data processing