Data Science 101

OCTOBER 31, 2019

A definition from the book ‘Data Mining: Practical Machine Learning Tools and Techniques’, written by, Ian Witten and Eibe Frank describes Data mining as follows: “ Data mining is the extraction of implicit, previously unknown, and potentially useful information from data. Clustering. Data Collection.

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PyImageSearch

JANUARY 9, 2023

Note that this entails a simple way multi-class classification problem for a database with personnel (here, persons or classes). In case of verification, we pre-extract and store the feature representation for all face images in our database, as shown. Figure 3: Face Verification (source: image by the author).

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Deep Learning Deep Learning Database Algorithm 103

Hacker News

APRIL 18, 2021

A touchscreen interface that's super laggy, or an appointment booking app that forces you to go in and out of possible dates and fill in all information before it tells you if it's available. The word cluster is an anachronism to an end-user in the cloud! Do you need a database for your test suite? I used to think this was fine!

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Snorkel AI

SEPTEMBER 20, 2023

For example, if a data team wants to use an LLM to examine financial documents—something the model may perform poorly on out of the box—the team can fine-tune it on something like the Financial Documents Clustering data set. This information could come from: A vector database such as FAISS or Pinecone. Book a demo today.

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AWS Machine Learning Blog

FEBRUARY 13, 2024

We used FSx for Lustre and Amazon Relational Database Service (Amazon RDS) for fast parallel data access. Sudhanshu has to his credit a couple of patents; has written 2 books, several papers, and blogs; and has presented his point of view in various forums. Store data in an Amazon Simple Storage Service (Amazon S3) bucket.

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Mlearning.ai

JULY 25, 2023

Case Study Book in Progress! Below is a link to the book outline, Data Science Observations in a Chaotic World , feel free to let me know what you think! From a modeling and coding perspective, preparing case studies may seem time consuming and boring, but it is important to know how to convey results in a clear and concise manner.

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AWS Machine Learning Blog

FEBRUARY 14, 2024

In this post, we discuss how to use the comprehensive capabilities of Amazon Bedrock to perform complex business tasks and improve the customer experience by providing personalization using the data stored in a database like Amazon Redshift. This solution contains two major components. This solution contains two major components.

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PyImageSearch

SEPTEMBER 30, 2024

Orchestration Tools: Kubernetes, Docker Swarm Purpose: Manages the deployment, scaling, and operation of application containers across clusters of hosts. Inside you'll find my hand-picked tutorials, books, courses, and libraries to help you master CV and DL! Orchestration tools automate the scheduling and coordination of containers.

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Hacker News

MARCH 20, 2023

This line of thought was strengthened, a few months later, by codelike writings in a book that came to be associated with the case. The police asked the public for copies of the book in which the final page had been torn out. A man found such a book in his car, where apparently it had been thrown in through an open window.

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Database Clustering AI AI 182

Mlearning.ai

DECEMBER 21, 2023

Vectors are typically stored in Vector Databases which are best suited for searching. APIs File Directories Databases And many more The first step is to extract the information present in these source locations. For this we use a special kind of database called the Vector Database. What is a Vector Database?

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Pickl AI

JULY 31, 2024

Summary: MySQL is a widely used open-source relational database management system known for its reliability and performance. Overview of MySQL MySQL is one of the most popular relational database management systems (RDBMS) in the world, widely used for managing and organizing data.

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AWS Machine Learning Blog

MAY 30, 2024

In this post, we describe how CBRE partnered with AWS Prototyping to develop a custom query environment allowing natural language query (NLQ) prompts by using Amazon Bedrock, AWS Lambda , Amazon Relational Database Service (Amazon RDS), and Amazon OpenSearch Service. Embeddings were generated using Amazon Titan.

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AWS Machine Learning Blog

JANUARY 31, 2024

Amazon Titan Text Embeddings is a text embeddings model that converts natural language text—consisting of single words, phrases, or even large documents—into numerical representations that can be used to power use cases such as search, personalization, and clustering based on semantic similarity. Nitin Eusebius is a Sr.

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Natural Language Processing AWS Machine Learning Machine Learning 128

DagsHub

MARCH 19, 2024

As you can see, the ImageNet database revolutionized computer vision and has become a catalyst for computer vision tasks! Tesla, for instance, relies on a cluster of NVIDIA A100 GPUs to train their vision-based autonomous driving algorithms. Therefore, in 2024, you will very much run into apps driven by computer vision.

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

The following figure illustrates the idea of a large cluster of GPUs being used for learning, followed by a smaller number for inference. The State of AI Report gives the size and owners of the largest A100 clusters, the top few being Meta with 21,400, Tesla with 16,000, XTX with 10,000, and Stability AI with 5,408.

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Mlearning.ai

JUNE 8, 2023

Like traditional database index, vector index organizes the vectors into a data structure and makes it possible to navigate through the vectors and find the ones that are closest in terms of semantic similarity. Clustering  — we can cluster our sentences, useful for topic modeling. The main difference is in the pre-training.

Machine Learning 52

Machine Learning Machine Learning Clustering Database 52

Heartbeat

NOVEMBER 6, 2023

To understand this, imagine you have a pipeline that extracts weather information from an API, cleans the weather information, and loads it into a database. Airflow has four major components, which are The Scheduler The Worker A Database A web server The four major components work in sync to manage data pipelines in Apache Airflow.

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IBM Journey to AI blog

JULY 1, 2024

In her book, Data lineage from a business perspective , Dr. Irina Steenbeek introduces the concept of descriptive lineage as “a method to record metadata-based data lineage manually in a repository.” Unfortunately, descriptive lineage doesn’t get the attention or recognition it deserves.

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ODSC - Open Data Science

JULY 11, 2023

For HPC, it’s possible to use a cluster of powerful workstations or servers, each with multiple processors and large amounts of memory. Users who want to dig much deeper with other sources of text can find several books about data centers on Amazon.com or elsewhere. The 11 most essential books for data center directors, on [link] 11.

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Data Lakes AI AI Cloud Computing 40

O'Reilly Media

OCTOBER 19, 2021

Adapted from the book Effective Data Science Infrastructure. Prior to the cloud, setting up and operating a cluster that can handle workloads like this would have been a major technical challenge. The intention behind the examples is not to be comprehensive (perhaps a fool’s errand, anyway!), Foundational Infrastructure Layers.

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Mlearning.ai

JANUARY 17, 2024

Traditional AI can recognize, classify, and cluster, but not generate the data it is trained on. Stacks of books and scrolls next to him and behind him. Let’s play the comparison game. If classic AI is the wise owl, generative AI is the wiser owl with a paintbrush and a knack for writing. Suprisingly small (7B params).

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Hacker News

JANUARY 9, 2024

I was able to write a book of manageable size that could pretty much explain the whole system. with all the functionality it contains—one would need a book with perhaps 200,000 pages. And in a similar vein, we can expect LLMs to be useful in making connections to external databases, functions, etc. But for Version 14.0—with

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AWS Machine Learning Blog

NOVEMBER 30, 2023

Nobody else offers this same combination of choice of the best ML chips, super-fast networking, virtualization, and hyper-scale clusters. Customers are telling us that Neuron has made it easy for them to switch their existing model training and inference pipelines to Trainium and Inferentia with just a few lines of code.

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Flipboard

NOVEMBER 24, 2023

The SnapLogic Intelligent Integration Platform (IIP) enables organizations to realize enterprise-wide automation by connecting their entire ecosystem of applications, databases, big data, machines and devices, APIs, and more with pre-built, intelligent connectors called Snaps.

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AWS Machine Learning Blog

JULY 20, 2023

Examination of this data is critical for monitoring the state of the power grid, identifying infrastructure anomalies, and updating databases of installed assets, and it allows granular control of the infrastructure down to the material and status of the smallest insulator installed on a given pole.

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Mlearning.ai

AUGUST 18, 2023

Image from Wallpaper Flare Let’s say you are in a huge library and you want to find a book with a specific topic like “Machine Learning”. With no help, you’d have to go through every single book in the library, which would take a long time. In a library, there is a catalog that lists all the books and what they’re about.

SQL 52

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phData

NOVEMBER 9, 2023

As an example, an IT team could easily take the knowledge of database deployment from on-premises and deploy the same solution in the cloud on an always-running virtual machine. Book a strategy session The post What is the Snowflake Data Cloud and How Much Does it Cost?

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AWS Machine Learning Blog

OCTOBER 23, 2024

Agent Creator is a versatile extension to the SnapLogic platform that is compatible with modern databases, APIs, and even legacy mainframe systems, fostering seamless integration across various data environments. The resulting vectors are stored in OpenSearch Service databases for efficient retrieval and querying.

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AI AI AWS Database 71

DagsHub

JULY 15, 2024

Data is chunked into smaller pieces and stored in a vector database, enabling efficient retrieval based on semantic similarity. They can engage users in natural dialogue, provide customer support, answer FAQs, and assist with booking or shopping decisions. You can automatically manage and monitor your clusters using AWS, GCD, or Azure.

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