Based on our record, Pandas seems to be a lot more popular than Amazon Forecast. While we know about 198 links to Pandas, we've tracked only 4 mentions of Amazon Forecast. 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
Python is a natural fit for serverless development. It boasts a vast array of libraries, including Powertools for AWS and robust libraries for data engineers. Its versatility and excellent developer experience make it a top choice for serverless projects, offering a seamless and enjoyable development experience. - Source: dev.to / 13 days ago
In data analysis, managing the structure and layout of data before analyzing them is crucial. Python offers versatile tools to manipulate data, including the often-used Pandas reset_index() method. - Source: dev.to / 7 days ago
Dash is a Python framework that enables you to build interactive frontend applications without writing a single line of Javascript. Internally and in projects we like to use it in order to build a quick proof of concept for data driven applications because of the nice integration with Plotly and pandas. For this post, I'm going to assume that you're already familiar with Dash and won't explain that part in detail.... - Source: dev.to / 2 months ago
Last year I worked through the challenges using VisiData, Datasette, and Pandas. I walked through my thought process and solutions in a series of posts. - Source: dev.to / 5 months ago
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks. - Source: dev.to / 5 months ago
Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
NumPy - NumPy is the fundamental package for scientific computing with Python
machine-learning in Python - Do you want to do machine learning using Python, but you’re having trouble getting started? In this post, you will complete your first machine learning project using Python.
Google Cloud TPU - Custom-built for machine learning workloads, Cloud TPUs accelerate training and inference at scale.
OpenCV - OpenCV is the world's biggest computer vision library
AWS Personalize - Real-time personalization and recommendation engine in AWS