Remove 2008 Remove Natural Language Processing Remove Python
article thumbnail

Getting Started with AI

Towards AI

Mirjalili, Python Machine Learning, 2nd ed. McKinney, Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython, 2nd ed., Natural Language Processing with Python — Analyzing Text with the Natural Language Toolkit. 2008 (2nd edition). Speech and Language Processing.

article thumbnail

70+ Best and Unique Python Machine Learning Projects with source code [2023]

Mlearning.ai

In today’s blog, we will see some very interesting Python Machine Learning projects with source code. This is one of the best Machine learning projects in Python. Doctor-Patient Appointment System in Python using Flask Hey guys, in this blog we will see a Doctor-Patient Appointment System for Hospitals built in Python using Flask.

professionals

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Zero-shot prompting for the Flan-T5 foundation model in Amazon SageMaker JumpStart

AWS Machine Learning Blog

We also demonstrate how you can engineer prompts for Flan-T5 models to perform various natural language processing (NLP) tasks. Task Prompt (template in bold) Model output Summarization Briefly summarize this paragraph: Amazon Comprehend uses natural language processing (NLP) to extract insights about the content of documents.

article thumbnail

Accelerate development of ML workflows with Amazon Q Developer in Amazon SageMaker Studio

AWS Machine Learning Blog

This dataset contains 10 years (1999–2008) of clinical care data at 130 US hospitals and integrated delivery networks. For instance, instead of a vague query about AWS services, try: “Can you provide sample code using the SageMaker Python SDK library to train an XGBoost model in SageMaker?” Let’s start with data exploration.

ML 79
article thumbnail

Financial text generation using a domain-adapted fine-tuned large language model in Amazon SageMaker JumpStart

AWS Machine Learning Blog

Large language models (LLMs) with billions of parameters are currently at the forefront of natural language processing (NLP). These models are shaking up the field with their incredible abilities to generate text, analyze sentiment, translate languages, and much more.

ML 75
article thumbnail

Domain-adaptation Fine-tuning of Foundation Models in Amazon SageMaker JumpStart on Financial data

AWS Machine Learning Blog

Large language models (LLMs) with billions of parameters are currently at the forefront of natural language processing (NLP). These models are shaking up the field with their incredible abilities to generate text, analyze sentiment, translate languages, and much more.

ML 52
article thumbnail

A review of purpose-built accelerators for financial services

AWS Machine Learning Blog

In terms of resulting speedups, the approximate order is programming hardware, then programming against PBA APIs, then programming in an unmanaged language such as C++, then a managed language such as Python. Analysis of publications containing accelerated compute workloads by Zeta-Alpha shows a breakdown of 91.5%

AWS 92