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machine-learning in Python
Scikit-learn
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python-recsys
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Amazon Forecast| Categories |
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| Website | aws.amazon.com |
machine-learning in Python| Categories |
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| Website | machinelearningmastery.com |
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Based on our record, machine-learning in Python should be more popular than Amazon Forecast. It has been mentiond 7 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.
Generative Artificial Intelligence (GenAI) is a type of artificial intelligence that can generate text, images, or other media using generative models. AWS offers a range of services for building and scaling generative AI applications, including Amazon SageMaker, Amazon Rekognition, AWS DeepRacer, and Amazon Forecast. AWS has also invested in developing foundation models (FMs) for generative AI, which are... - Source: dev.to / 3 months ago
In this reproducible experiment, we compare Amazon Forecast and StatsForecast a python open-source library for statistical methods. Source: over 1 year ago
It sounds like you need something that mostly runs itself, without you necessarily needing to have in-depth knowledge of time series modeling. If you have an AWS account, I'd recommend checking out Amazon Forecast. One of the recommendations I saw in this thread is to run auto.arima in R. That's actually one of the algorithms AWS will run for you, among others. I don't know if it handles differencing and... Source: over 2 years ago
With the help of Amazon Forecast, the forecasting technology at the heart of Amazon.com, it is now possible to build forecasting models for your own applications. - Source: dev.to / about 3 years ago
After that you should probably look at some very basic ML tutorials. I just googled it, I have no idea if this is good https://machinelearningmastery.com/machine-learning-in-python-step-by-step/. Source: about 1 year ago
Few different approaches based on search engine 'ml with python': Work though use cases / examples : https://www.databricks.com/resources/ebook/big-book-of-machine-learning-use-cases On-line class(es) / step by step projects: * https://bootcamp-sl.discover.online.purdue.edu/ai-machine-learning-certification-course * https://www.w3schools.com/python/python_ml_getting_started.asp *... - Source: Hacker News / about 1 year ago
MLE: ALL OF THE ABOVE (this is important - pure machine learning skills generally won’t make you hireable unless you’re doing a PhD and/or are a genius) Plus: 1. https://machinelearningmastery.com/machine-learning-in-python-step-by-step/ 2. https://www.coursera.org/learn/machine-learning 3. https://www.3blue1brown.com/topics/neural-networks. Source: almost 2 years ago
Have you seen this? https://machinelearningmastery.com/machine-learning-in-python-step-by-step/. Source: over 2 years ago
Machine learning models Fine-tune existing machine learning models for improved accuracy, or create your own custom models. - Source: dev.to / over 2 years ago
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
Google Cloud TPU - Custom-built for machine learning workloads, Cloud TPUs accelerate training and inference at scale.
BigML - BigML's goal is to create a machine learning service extremely easy to use and seamless to integrate.
AWS Personalize - Real-time personalization and recommendation engine in AWS
python-recsys - python-recsys is a python library for implementing a recommender system.
Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.