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The mystery of indexing – A guide to different types of indexes in Python

Data Science Dojo

Using the “Top Spotify songs from 2010-2019” dataset on Kaggle ( [link] ), we read it into a Python – Pandas Data Frame. This is a default index created by python for this dataset, while considering the first column present in the csv file as an “unnamed” column. You may only build a single Primary or Clustered index on a table.

Python 369
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Racing into the future: How AWS DeepRacer fueled my AI and ML journey

AWS Machine Learning Blog

In 2018, I sat in the audience at AWS re:Invent as Andy Jassy announced AWS DeepRacer —a fully autonomous 1/18th scale race car driven by reinforcement learning. For 2018, because AWS DeepRacer had just been unveiled, re:Invent attendees could compete in person at the MGM Grand using pre-trained models.

AWS 110
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Fast and cost-effective LLaMA 2 fine-tuning with AWS Trainium

AWS Machine Learning Blog

Our high-level training procedure is as follows: for our training environment, we use a multi-instance cluster managed by the SLURM system for distributed training and scheduling under the NeMo framework. From 2015–2018, he worked as a program director at the US NSF in charge of its big data program. Youngsuk Park is a Sr.

AWS 131
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How Sportradar used the Deep Java Library to build production-scale ML platforms for increased performance and efficiency

AWS Machine Learning Blog

Right now, most deep learning frameworks are built for Python, but this neglects the large number of Java developers and developers who have existing Java code bases they want to integrate the increasingly powerful capabilities of deep learning into. Business requirements We are the US squad of the Sportradar AI department.

ML 98
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Fine-tune and deploy Llama 2 models cost-effectively in Amazon SageMaker JumpStart with AWS Inferentia and AWS Trainium

AWS Machine Learning Blog

Solution overview In this blog, we will walk through the following scenarios : Deploy Llama 2 on AWS Inferentia instances in both the Amazon SageMaker Studio UI, with a one-click deployment experience, and the SageMaker Python SDK. Fine-tune Llama 2 on Trainium instances in both the SageMaker Studio UI and the SageMaker Python SDK.

AWS 134
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Linear Regression for tech start-up company Cars4U in Python

Mlearning.ai

In 2018–2019, while new car sales were recorded at 3.6 These are common Python libraries used for data analysis and visualization. The next step post that would be to cluster different sets of data and see if multiple models should be created for different locations and car types. I hope you enjoyed this post.

Python 52
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A review of purpose-built accelerators for financial services

AWS Machine Learning Blog

The following figure illustrates the idea of a large cluster of GPUs being used for learning, followed by a smaller number for inference. In 2018, other forms of PBAs became available, and by 2020, PBAs were being widely used for parallel problems, such as training of NN. GPU PBAs, 4% other PBAs, 4% FPGA, and 0.5%

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