Flipboard

FEBRUARY 2, 2023

With advanced analytics derived from machine learning (ML), the NFL is creating new ways to quantify football, and to provide fans with the tools needed to increase their knowledge of the games within the game of football. We then explain the details of the ML methodology and model training procedures.

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AWS Machine Learning Blog

JUNE 26, 2024

This blog is part of the series, Generative AI and AI/ML in Capital Markets and Financial Services. Lambda natively supports Java, Go, PowerShell, Node.js, C#, Python, and Ruby code. Prompt the agent to build an optimal portfolio using the collected data What are the closing prices of stocks AAAA, WWW, DDD in year 2018?

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ODSC - Open Data Science

SEPTEMBER 21, 2023

The following is an extract from Andrew McMahon’s book , Machine Learning Engineering with Python, Second Edition. Secondly, to be a successful ML engineer in the real world, you cannot just understand the technology; you must understand the business. What does an ML solution look like?

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AWS Machine Learning Blog

MAY 31, 2023

Actually, you can develop such a system using state-of-the-art language models and a few lines of Python. In 2018, BERT-large made its debut with its 340 million parameters and innovative transformer architecture, setting the benchmark for performance on NLP tasks. To make it easier to see the prompt, you can enlarge the Prompt box.

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AWS Machine Learning Blog

JANUARY 17, 2024

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.

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AWS Machine Learning Blog

NOVEMBER 8, 2023

The MONAI AI models and applications can be hosted on Amazon SageMaker , which is a fully managed service to deploy machine learning (ML) models at scale. The AHItoDICOM class takes advantage of multiple processes to retrieve pixel frames from AWS HealthImaging in parallel, and decode the HTJ2K binary blobs using the Python OpenJPEG library.

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Towards AI

JULY 19, 2023

The Continuing Story of Neural Magic Around New Year’s time, I pondered about the upcoming sparsity adoption and its consequences on inference w/r/t ML models. Their infrastructure is built on top of FastAPI and supports Python, Go and Ruby languages. and share with friends! The company is Neural Magic. You can read their blog post ?

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Towards AI

JULY 4, 2024

If you are good with Python, AI, ML, APIs, py-cord, or setting up a machine/server, connect with him in the Discord thread! Introduced in 2018, BERT has been a topic of interest for many, with many articles and YouTube videos attempting to break it down. Keep an eye on this section, too — we share cool opportunities every week!

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

These activities cover disparate fields such as basic data processing, analytics, and machine learning (ML). ML is often associated with PBAs, so we start this post with an illustrative figure. The ML paradigm is learning followed by inference. The union of advances in hardware and ML has led us to the current day.

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AWS Machine Learning Blog

AUGUST 7, 2023

AWS ProServe solved this use case through a joint effort between the Generative AI Innovation Center (GAIIC) and the ProServe ML Delivery Team (MLDT). However, LLMs are not a new technology in the ML space. The new ML workflow now starts with a pre-trained model dubbed a foundation model.

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AWS Machine Learning Blog

APRIL 3, 2023

Causal inference Causality is all about understanding change, but how to formalize this in statistics and machine learning (ML) is not a trivial exercise. Note that this solution is currently available in the US West (Oregon) Region only. In this crop yield study, the nitrogen added as fertilizer and the yield outcomes might be confounded.

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AWS Machine Learning Blog

NOVEMBER 14, 2023

Examples include: Cultivating distrust in the media Undermining the democratic process Spreading false or discredited science (for example, the anti-vax movement) Advances in artificial intelligence (AI) and machine learning (ML) have made developing tools for creating and sharing fake news even easier.

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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. Clay Elmore is an AI/ML Specialist Solutions Architect at AWS.

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AWS Machine Learning Blog

AUGUST 16, 2023

Training machine learning (ML) models to interpret this data, however, is bottlenecked by costly and time-consuming human annotation efforts. The images document the land cover, or physical surface features, of ten European countries between June 2017 and May 2018. The following are a few example RGB images and their labels.

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AWS Machine Learning Blog

JUNE 5, 2023

In this post, we show you how to train the 7-billion-parameter BloomZ model using just a single graphics processing unit (GPU) on Amazon SageMaker , Amazon’s machine learning (ML) platform for preparing, building, training, and deploying high-quality ML models. BloomZ is a general-purpose natural language processing (NLP) model.

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Mlearning.ai

FEBRUARY 28, 2023

In 2018–2019, while new car sales were recorded at 3.6 These are common Python libraries used for data analysis and visualization. Submission Suggestions Linear Regression for tech start-up company Cars4U in Python was originally published in MLearning.ai million units, around 4 million second-hand cars were bought and sold.

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Towards AI

JULY 21, 2023

Instead of building a model from… github.com NERtwork Awesome new shell/python script that graphs a network of co-occurring entities from plain text! It uses the 2 model architecture: sparse search via Elasticsearch and then a ranker ML model. Obama and Barrack are same entity) and NetworkX for graph creation.

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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 Yearly average sales. Convert it into a graph.

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Pickl AI

MAY 16, 2023

Python, Data Mining, Analytics and ML are one of the most preferred skills for a Data Scientist. For example, if you are a Data Scientist, then you should add keywords like Python, SQL, Machine Learning, Big Data and others. Expansive Hiring The IT and service sector is actively hiring Data Scientists. Wrapping it up !!!

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Mlearning.ai

MAY 5, 2023

Introduction of Large Language Models One of the most influential LLMs is the GPT (Generative Pre-trained Transformer) model, which was first introduced by OpenAI in 2018. Programming Skills : LLMs are typically developed using programming languages like Python, so it’s essential to have strong programming skills.

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Pickl AI

APRIL 10, 2023

As per the recent report by Nasscom and Zynga, the number of data science jobs in India is set to grow from 2,720 in 2018 to 16,500 by 2025. In addition, you also have other Data Science programs available on the platform, like PG Program in AI and ML, PGP in Data Science and Engineering (Bootcamp), and others. In addition, Pickl.AI

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AWS Machine Learning Blog

MAY 5, 2023

Solution overview Ground Truth is a fully self-served and managed data labeling service that empowers data scientists, machine learning (ML) engineers, and researchers to build high-quality datasets. For our example use case, we work with the Fashion200K dataset , released at ICCV 2017.

Machine Learning 101

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Heartbeat

MARCH 14, 2023

Some recent examples: Robotic systems that learned to grab and manipulate things with human-like dexterity was demonstrated by Google Brain researchers in 2018 utilizing deep reinforcement learning. Deep learning for computer vision with Python. Additional resources: Adrian, R. We pay our contributors, and we don’t sell ads.

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Towards AI

JULY 21, 2023

The Continuing Story of Neural Magic Around New Year’s time, I pondered about the upcoming sparsity adoption and its consequences on inference w/r/t ML models. Their infrastructure is built on top of FastAPI and supports Python, Go and Ruby languages. and share with friends! The company is Neural Magic. You can read their blog post ?

Natural Language Processing 52

Natural Language Processing Azure Python Artificial Intelligence 52

AWS Machine Learning Blog

NOVEMBER 21, 2023

Amazon Textract is a machine learning (ML) service that automatically extracts text, handwriting, and data from any document or image. You can use either method to generate the linearized text from the document using the latest version of Amazon Textract Textractor Python library.

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Mlearning.ai

MARCH 9, 2023

2018; Sitawarin et al., 2018; Papernot et al., 2018) investigated the vulnerability of deep learning models to adversarial attacks in medical image segmentation tasks, and proposed a method to improve their robustness. 2018; Pang et al., For instance, Xu et al. Another study by Jin et al. Makelov, A., Schmidt, L.,

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Google Research AI blog

FEBRUARY 28, 2023

Adherence to such public health programs is a prevalent challenge, so researchers from Google Research and the Indian Institute of Technology, Madras worked with ARMMAN to design an ML system that alerts healthcare providers about participants at risk of dropping out of the health information program. certainty when used correctly.

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O'Reilly Media

NOVEMBER 28, 2023

If ChatGPT writes a Python script for you, you may not care why it wrote that particular script rather than something else. The next most needed skill is operations for AI and ML (54%). We’re glad to see people recognize this; we’ve long thought that operations was the “elephant in the room” for AI and ML.

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DrivenData Labs

DECEMBER 13, 2022

head () Out[4]: uid latitude longitude date split 0 aabm 39.080319 -86.430867 2018-05-14 train 1 aabn 36.559700 -121.510000 2016-08-31 test 2 aacd 35.875083 -78.878434 2020-11-19 train 3 aaee 35.487000 -79.062133 2016-08-24 train 4 aaff 38.049471 -99.827001 2019-07-23 train In [5]: metadata. python train_gbm_model.py value_counts ().

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Mlearning.ai

JULY 31, 2023

One example is the Pairwise Inner Product (PIP) loss, a metric designed to measure the dissimilarity between embeddings using their unitary invariance (Yin and Shen, 2018). Yin and Shen (2018) accompany their research with a code implementation on GitHub here. Fortunately, there is; use an embedding loss. Equation 2.3.1. Shazeer, N.,

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Mlearning.ai

FEBRUARY 10, 2023

I have 2 years of experience working as a machine learning and python developer. In the next article, I will discuss how you can identify and address your error using the insight from the learning curve. References [1].Ng, Ng, Andrew. Machine learning yearning. URL: htts://info. deeplearning.ai/machine-learning-yearning-book Java Point.

Machine Learning 52

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Snorkel AI

MAY 12, 2023

Please welcome to the stage, Senior Director of Applied ML and Research, Bayan Bruss; Director of Data Science, Erin Babinski; and Head of Data and Machine Learning, Kishore Mosaliganti. All right, so let’s set the stage first with some examples: a focus on data quality leads to better ML-powered products. That’s data.

Machine Learning 52

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Snorkel AI

MAY 12, 2023

Please welcome to the stage, Senior Director of Applied ML and Research, Bayan Bruss; Director of Data Science, Erin Babinski; and Head of Data and Machine Learning, Kishore Mosaliganti. All right, so let’s set the stage first with some examples: a focus on data quality leads to better ML-powered products. That’s data.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Explosion

MAY 17, 2023

Transformers makes it easy to use a wide variety of models from recent research, and it’s closer to the underlying ML library (PyTorch). In my opinion the best things to read on this are articles from when the developments were relatively fresh, such as Sebastian Ruder’s 2018 blog post NLP’s ImageNet moment has finally arrived.

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Heartbeat

SEPTEMBER 13, 2023

Here's an example of calculating feature importance using permutation importance with scikit-learn in Python: from sklearn.inspection import permutation_importance # Fit your model (e.g., Alibi Alibi is an open-source Python library for algorithmic transparency and interpretability. Russell, C. & & Watcher, S.

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AWS Machine Learning Blog

MAY 22, 2023

Fine-tune FLAN-T5 using a Python notebook Our example notebook shows how to use Jumpstart and SageMaker to programmatically fine-tune and deploy a FLAN T5 XL model. These include research on foundation models, as well as ML applications for graphs and time series. He loves developing user friendly ML systems.

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Mlearning.ai

JUNE 8, 2023

machine learning models that learn from almost no training data) Fraud detection/outlier detection Typo detection and all manners of “fuzzy matching” Detecting when ML models go stale (drift) Learning embeddings for your machine learning model An embedding is a mapping from discrete objects, such as words, to vectors of real numbers.

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