Explosion

DECEMBER 17, 2013

A concise sample implementation is provided, in 500 lines of Python, with no external dependencies. In 2015 this type of parser is now increasingly dominant. This post explains how transition-based dependency parsers work, and argues that this algorithm represents a break-through in natural language understanding.

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Mlearning.ai

APRIL 25, 2023

In today’s blog, we will explore the Netflix dataset using Python and uncover some interesting insights. In this blog, we’ll be using Python to perform exploratory data analysis (EDA) on a Netflix dataset that we’ve found on Kaggle. Submission Suggestions Netflix Data Analysis using Python was originally published in MLearning.ai

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phData

SEPTEMBER 20, 2023

Snowpark is the set of libraries and runtimes in Snowflake that securely deploy and process non-SQL code, including Python , Java, and Scala. On the server side, runtimes include Python, Java, and Scala in the warehouse model or Snowpark Container Services (private preview). Why is Snowpark Exciting to us?

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Towards AI

APRIL 7, 2024

Gilead Sciences provided a rich, real-world dataset that contains information about demographics, diagnosis and treatment options, and insurance provided to patients who were diagnosed with breast cancer from 2015–2018. The dataset originated from Health Verity, one of the largest healthcare data ecosystems in the US.

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ODSC - Open Data Science

FEBRUARY 20, 2023

Rumelhart Prize in 2015, and the ACM/AAAI Allen Newell Award in 2009. He received the Ulf Grenander Prize from the American Mathematical Society in 2021, the IEEE John von Neumann Medal in 2020, the IJCAI Research Excellence Award in 2016, the David E.

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Towards AI

AUGUST 8, 2024

Developed by Google in 2015, TensorFlow boasts extensive capabilities, resulting in the tool being used often for research purposes or companies using it for their programming purposes. It can also be used in a variety of languages, such as Python, C++, JavaScript, and Java.

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Towards AI

APRIL 19, 2024

Intelligent Medical Objects 👉Industry domain: AI, Health Tech, IT, NLP, Software, Analytics, Generative AI 👉Location: 3 offices 👉Year founded: 1994 👉Programming languages deployed: Angular, C#, SQL, Scikit, TensorFlow, Spark, GitHub, R, Python 👉Benefits: Flexible time off, family medical leave, pet insurance, (..)

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Flipboard

SEPTEMBER 4, 2023

Container runtimes are consistent, meaning they would work precisely the same whether you’re on a Dell laptop with an AMD CPU, a top-notch MacBook Pro , or an old Intel Lenovo ThinkPad from 2015. Alternative NVIDIA NGC Container Image here ) Python The container runtime for Python sets up a Debian Linux instance with Python pre-installed.

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AWS Machine Learning Blog

AUGUST 5, 2024

To make API calls to Amazon Bedrock from our generative AI application, we use Python version 3.11.4 and the AWS SDK for Python (Boto3). In episode 20, titled “AI Accelerators in the Cloud,” our guest Matthew McClean, a senior manager from AWS’s Annapurna team, shared why AWS decided to buy Annapurna Labs in 2015.

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AWS Machine Learning Blog

NOVEMBER 19, 2024

Reserve your seat now AIM406: Attain ML excellence with proficiency in Amazon SageMaker Python SDK December Wednesday 4 |4:30 PM – 5:30 PM In this comprehensive code talk, delve into the robust capabilities of the Amazon SageMaker Python SDK.

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PyImageSearch

NOVEMBER 13, 2023

2015 ), SSD ( Fei-Fei et al., 2015 ; Redmon and Farhad, 2016 ), and others. If you’re interested in learning more about IoU, including a walkthrough of Python code demonstrating how to implement it, please see our earlier blog post. Image credit: Figure 1 of Girshick (2015) ). In this work, Girshick et al.

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Mlearning.ai

MAY 15, 2023

describe() count 9994 mean 2017-04-30 05:17:08.056834048 min 2015-01-03 00:00:00 25% 2016-05-23 00:00:00 50% 2017-06-26 00:00:00 75% 2018-05-14 00:00:00 max 2018-12-30 00:00:00 Name: Order Date, dtype: object Average sales per year df['year'] = df['Order Date'].apply(lambda Latest order date. Yearly average sales.

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AWS Machine Learning Blog

OCTOBER 9, 2023

For this post, we choose Python (User-Defined Function). Choose Python as the mode for the transformation and insert the following code for the Python function: def custom_func(value: int) → str: return datetime.utcfromtimestamp(value).strftime('%Y-%m-%d We can do this by adding a Custom transform step. DOI= [link]

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AWS Machine Learning Blog

NOVEMBER 21, 2023

python -m pip install -q amazon-textract-prettyprinter You have the option to format the text in markdown format, exclude text from within figures in the document, and exclude page header, footer, and page number extractions from the linearized output. At this event, SPIE member Light and Light-based Technologies (IYL 2015).

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Towards AI

AUGUST 11, 2023

A small startup named OpenAI got formed then after a year, in Dec 2015. Using the code interpreter, you could now run Python programs in ChatGPT, upload and even download files. Facebook then, on the other hand, was creating a system that could predict if two picture showed the same person.

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AWS Machine Learning Blog

AUGUST 11, 2023

You will learn how to use the SageMaker Jumpstart UI and SageMaker Python SDK to deploy the solution and run inference using the available models. For this solution, we use the 2015 New Year’s Resolutions dataset to classify resolutions. The following diagram illustrates the architecture of this method.

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AWS Machine Learning Blog

OCTOBER 20, 2023

Meesho was founded in 2015 and today focuses on buyers and sellers across India. We used Dask—a distributed data science computing framework that natively integrates with Python libraries—on Amazon EMR to scale out the training jobs across the cluster. One of the major challenges was to run distributed training at scale.

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Towards AI

SEPTEMBER 28, 2023

The data at our disposal ranges from January 2015 to April 2023, totaling more than 153,000 transactions. In Python, we construct a heterogeneous graph using the HeteroData object from the PyTorch Geometric (PyG) library. [4] Since each trade is logged twice, we focus on exports. Sequence of monthly snapshots.

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Pickl AI

JANUARY 23, 2023

It supports languages like Python and R and processes the data with the help of data flow graphs. It is an open-source framework that is written in Python and can efficiently operate on both GPUs and CPUs. Keras supports a high-level neural network API written in Python. It is an open source framework.

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AWS Machine Learning Blog

OCTOBER 5, 2023

For example, to use the RedPajama dataset, use the following command: wget [link] python nemo/scripts/nlp_language_modeling/preprocess_data_for_megatron.py From 2015–2018, he worked as a program director at the US NSF in charge of its big data program. He founded StylingAI Inc., Before joining the industry, he was the Charles E.

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Explosion

NOVEMBER 21, 2019

In 2016 we trained a sense2vec model on the 2015 portion of the Reddit comments corpus, leading to a useful library and one of our most popular demos. Try the new interactive demo to explore similarities and compare them between 2015 and 2019 sense2vec (Trask et. Interestingly, “to ghost” wasn’t very common in 2015.

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Mlearning.ai

MARCH 9, 2023

2015; Huang et al., 2015), which consists of 20 object categories with varying levels of complexity. We implemented the MBD approach using the Python programming language, with the scikit-learn and NetworkX libraries for feature selection and structure learning, respectively. 2012; Otsu, 1979; Long et al., 2018; Pang et al.,

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Hacker News

JANUARY 9, 2024

One very simple example (introduced in 2015) is Nothing : Another, introduced in 2020, is Splice : An old chestnut of Wolfram Language design concerns the way infinite evaluation loops are handled. There’s one setup for interpreted languages like Python. Let’s start with Python. And in Version 13.2 But in Version 14.0

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Mlearning.ai

JUNE 5, 2023

Note : This blog is more biased towards python as it is the language most developers use to get started in computer vision. Python / C++ The programming language to compose our solution and make it work. Why Python? Easy to Use: Python is easy to read and write, which makes it suitable for beginners and experts alike.

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Towards AI

JULY 19, 2023

196–210, 2015. Fieguth, “A review on computer vision-based defect detection and condition assessment of concrete and asphalt civil infrastructure,” Advanced Engineering Informatics, vol. View at: Publisher Site | Google Scholar B. Yi, and J.-K. 567–577, 2013.

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Explosion

MAY 10, 2016

The pay-off is the.pipe() method, which adds data-streaming capabilities to spaCy: import spacy nlp = spacy.load('de') for doc in nlp.pipe(texts, n_threads=16, batch_size=10000): analyse_text(doc) My favourite post on the Zen of Python iterators was written by Radim, the creator of Gensim. The Python unicode object is also very useful.

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Pickl AI

AUGUST 22, 2024

Discover its dynamic computational graphs, ease of debugging, strong community support, and seamless integration with popular Python libraries for enhanced development. Pythonic Nature PyTorch is designed to be intuitive and closely resembles standard Python programming.

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DagsHub

JULY 25, 2024

TensorFlow The Google Brain team created the open-source deep learning framework TensorFlow, which was made available in 2015. A good understanding of Python and machine learning concepts is recommended to fully leverage TensorFlow's capabilities. Before using Keras, ensure you have a basic understanding of Python and neural networks.

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Women in Big Data

MAY 21, 2024

Launched in 2015 and becoming a nonprofit organization in 2020, WiBD is a grassroots initiative dedicated to inspiring, connecting, and advancing women in data fields. Preparation: Completed the Data Engineer in Python track, dedicating at least one hour a day to study and take notes. She joined us to share her experience.

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AWS Machine Learning Blog

APRIL 25, 2024

Evaluate Claude v2 on summarization accuracy using Amazon Bedrock The following code snippet is an example of how to interact with the Anthropic Claude model using Python code: import json # We use Claude v2 in this example. # In this section, we demonstrate how to use the FMEval library.

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Flipboard

NOVEMBER 24, 2023

This use case highlights how large language models (LLMs) are able to become a translator between human languages (English, Spanish, Arabic, and more) and machine interpretable languages (Python, Java, Scala, SQL, and so on) along with sophisticated internal reasoning.

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Hacker News

MARCH 19, 2025

The Allen Institute for AI introduced Semantic Scholar way back in 2015; it was among the earliest platforms to rank and predict research relevance with machine learning rather than raw citation counts. Going from a demo in a Jupyter notebook (used to write Python code) to getting something that can run at scale is a lot of work.

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Heartbeat

JULY 24, 2023

pip install dicom2nifti In a Python shell type: import dicom2nifti dicom2nifti.convert_directory("path to.dcm images"," path where results to be stored") And boom! Koltun, “Multi-scale context aggregation by dilated convolutions,” arXiv preprint arXiv:1511.07122, 2015. [4] dcm format. Conversion of images from .dcm

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AWS Machine Learning Blog

FEBRUARY 28, 2023

When he’s not modernizing workloads for global enterprises, Yann plays piano, tinkers in React and Python, and regularly YouTubes about his cloud journey. Yann earned his Bachelors at The Juilliard School. Ramesh Dwarakanath is a Principal Solutions Architect at AWS based out of Boston, MA.

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Heartbeat

APRIL 23, 2023

SpaCy is a popular open-source NLP library developed in 2015 by Matthew Honnibal and Ines Montani, the founders of the software company Explosion. We can do this using pip, a package manager for Python: pip install spacy Step 2: Load the SpaCy model We also need to download a pre-trained language model for SpaCy. What is SpaCy?

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Dataconomy

MAY 8, 2023

Here are some of the milestones of AI drawing generators to today: DeepDream , which was made by Google in 2015, is one of the first and most well-known AI drawing generators. The language model for Stable Diffusion is a transformer, and it is implemented in Python.

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IBM Journey to AI blog

AUGUST 11, 2023

The term was originally coined in 2015 in a published research paper called, “Hidden Technical Debts in the Machine Learning System,” which highlighted common problems that arose when using machine learning for business applications. Build and train models—Here is where ML teams use Ops practices to make MLOps.

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