Netflix Tech

OCTOBER 16, 2019

By Ammar Khaku Introduction In a microservice architecture such as Netflix’s, propagating datasets from a single source to multiple downstream destinations can be challenging. One example displaying the need for dataset propagation: at any given time Netflix runs a very large number of A/B tests.

Datasets 75

Datasets Metadata Bytes Machine Learning 75

Tweag

APRIL 19, 2023

To allow innovation in medical imaging with AI, we need efficient and affordable ways to store and process these WSIs at scale. A single hospital makes many captures a day, producing terabytes of such data to store and process. But then, what if we need to read tens of thousands of WSIs, a few gigabytes each? _slides_specs.

Medical 60

Medical Process Cloud Bytes 60

ProjectPro

JANUARY 15, 2021

And honestly, there are a lot of real-world machine learning datasets around you that you can opt to start practicing your fundamental data science and machine learning skills, even without having to complete a comprehensive data science or machine learning course. Table of Contents What is a dataset in machine learning?

Datasets 40

Datasets Machine Learning Retail Banking 40

Snowflake

MAY 15, 2024

By analyzing vast datasets, gen AI allows companies to quickly determine customer preferences, behaviors, sentiments and trends. Personalizing customer experiences: Delivering a more personalized experience is an essential competitive differentiator in today’s crowded media marketplace.

Entertainment 93

Entertainment Media Datasets Algorithm 93

ProjectPro

FEBRUARY 16, 2023

At the core of such applications lies the science of machine learning, image processing, computer vision, and deep learning. As an example, consider the Facial Image Recognition System, it leverages the OpenCV Python library for implementing image processing techniques. What is OpenCV Python?

Python 98

Python Process Deep Learning Algorithm 98

Towards Data Science

MARCH 29, 2023

Turbo and GPT-4 to categorize datasets without the need for labeled data or model training, by prompting the model with data excerpts and category definitions. Especially useful was that the model could provide reasoning for its predictions which helped to identify improvements to the process. Is the Dataset in an Approved Category?

Datasets 64

Datasets Food Retail Hospitality 64

ProjectPro

FEBRUARY 5, 2021

Image classification , a subfield of computer vision helps in processing and classifying objects based on trained algorithms. Nonetheless, it is an exciting and growing field and there can't be a better way to learn the basics of image classification than to classify images in the MNIST dataset. instead of handwritten digits.

Datasets 40

Datasets Deep Learning Medical Algorithm 40

Cloudera

APRIL 1, 2024

Download the complimentary 2023 Gartner Magic Quadrant for Cloud Database Management Systems report. Download the complimentary 2023 Gartner Critical Capabilities for Analytics Report to view the technical scores of each vendor on the three key analytic use cases. Unlike software, ML models need continuous tuning.

Cloud 104

Cloud Unstructured Data Metadata Datasets 104

Knowledge Hut

FEBRUARY 29, 2024

Learning Data Analysis in Excel Data analysis is a process of inspecting, cleaning, transforming and modelling data with an objective of uncover the useful knowledge, results and supporting decision. Then, based on this information from the sample, defect or abnormality the rate for whole dataset is considered.

Data Science 98

Data Science Datasets Database Design Machine Learning 98

Knowledge Hut

MAY 3, 2024

Types of Machine Learning: Machine Learning can broadly be classified into three types: Supervised Learning: If the available dataset has predefined features and labels, on which the machine learning models are trained, then the type of learning is known as Supervised Machine Learning. A sample of the dataset is shown below.

Machine Learning 98

Machine Learning Algorithm Datasets Medical 98

Towards Data Science

OCTOBER 21, 2023

PyrOSM is a package that makes the process of reading in and working with OSM data much more efficient. Well, PyrOSM is build on Cython (C Python) and it uses faster libraries for deserializing OSM data as well as smaller optimizations like numpy arrays which allows it to process data fast. Let’s get into what this library can do! ?

Datasets 77

Datasets Data Data Science Python 77

Knowledge Hut

JANUARY 3, 2024

Data visualization is the process of understanding the data in a more detailed way, using graphical representations such as graphs and plots. The packages include Pandas for processing, Matplotib for visualization, seaborn for advanced visuals, and Numpy for calculations. In today’s age, a lot of data is being generated daily.

Python 98

Python Programming Language Datasets R (Programming) 98

Knowledge Hut

FEBRUARY 29, 2024

Some examples of the best python packages for data science available on anaconda are: Programming Language: Python and R Data Processing: Numpy and Pandas Data Visualization: Matplotlib and Seaborn Data Modelling: Scikit-learn and Tensorflow IDE: Spyder and Jupyter Notebook Features of Anaconda Data Science 1. Environment Commands a.

Data Science 52

Data Science Project Datasets Python 52

Marc Lamberti

NOVEMBER 23, 2022

DuckDB is an in-process OLAP DBMS written in C++ blah blah blah, too complicated. Local First, DuckDB is an in-process single-file database with no external dependencies. On the other hand, DuckDB is embedded in the host application process and manages a database stored in a single file. Let’s start simple, shall we?

Datasets 130

Datasets Python SQL Database 130

Towards Data Science

FEBRUARY 19, 2024

However, the full dataset is about 40GB, and trying to handle that much data on my little laptop, or even in a Colab notebook was a bit much, so I had to figure out a pipeline that could manage filtering and embedding a larger data set. Below is the full process I went through to get everything up and running.

AWS 60

AWS Building Bytes Python 60

Precisely

OCTOBER 5, 2023

Data enrichment is the process of combining first-party data from internal sources with third-party data from external sources or data from other internal systems. This process provides context that unlocks valuable hidden insights and reveals critical relationships that enhance your data’s overall value, accuracy, and reliability.

Raw Data 67

Raw Data Insurance Datasets Telecommunication 67

Knowledge Hut

MARCH 29, 2024

Agile Management Resumeworded Template Link: Agile Management (Download here) Why This Cover Letter Works: Highlights specific years of experience in implementing agile methodologies. Showcases a data-driven approach to continuous improvement and process optimization. Cover Letter Examples by Jobs 1.

Database-centric 52

Database-centric Programming Language BI Finance 52

Engineering at Meta

AUGUST 8, 2023

With PDL, we encourage the use of stronger passwords while minimizing the information revealed to the server in the password precheck process. Then the server will apply the same hash algorithm and blinding operation with secret key b to all the passwords from the leaked password dataset. Sharding the leaked password dataset.

Datasets 80

Datasets Bytes Algorithm Designing 80

Towards Data Science

JANUARY 26, 2023

Unfortunately, we don’t always have control over the data design process and sometimes have no choice but to work with the cards we’ve been dealt. Direct Download from Amazon S3 In this post, we will assume that we are downloading files directly from Amazon S3. There a number of methods for downloading a file to a local disk.

Cloud Storage 74

Cloud Storage Big Data Cloud AWS 74

Rockset

JUNE 6, 2023

Multiple copies of the dataset: Running multiple compute clusters on the same underlying dataset requires replicating the data onto each compute cluster. Scaling compute clusters would then depend on compute requirements alone, and would be more elastic as we don’t need to download the full dataset as part of each scaling operation.

Metadata 52

Metadata Datasets Architecture Algorithm 52

Rockset

MARCH 9, 2023

You can download Geth from the Ethereum website and install it according to the instructions for your operating system. Download the Ethereum blockchain : After installing Geth, run it by opening a terminal window and simply executing the “geth” command. Anyone can ingest these datasets into a datastore for efficient querying via SQL.

Amazon Web Services 52

Amazon Web Services Datasets AWS Google Cloud 52

Towards Data Science

AUGUST 29, 2023

Today, we will delve into the intricacies the problem of missing data , discover the different types of missing data we may find in the wild, and explore how we can identify and mark missing values in real-world datasets. Image by Author. Let’s consider an example. Image by Author. Image by Author.

Datasets 106

Datasets Machine Learning Data Data Science 106

Cloudera

JULY 19, 2023

Data processing workloads tend to be more sensitive to the performance of transferring data between Datanodes and the various applications that process it. OM’s rate of serving operations becomes critical at scale, supporting the workloads spanning the entire dataset stored.

Management 70

Management Metadata Datasets Architecture 70

Cloudera

MAY 19, 2021

This year, we expanded our partnership with NVIDIA , enabling your data teams to dramatically speed up compute processes for data engineering and data science workloads with no code changes using RAPIDS AI. Get the Dataset. The dataset can be downloaded from: [link]. See < [link] > for more details.

Machine Learning 137

Machine Learning Datasets Data Science Raw Data 137

ProjectPro

JANUARY 24, 2023

In this project, you should first download the famous Iris Dataset and implement Exploratory Data Analysis techniques over it. In this project, we suggest you build your own dataset by clicking the images of your family members. Most beginners in Data Science and Machine learning have worked on this dataset.

Project 52

Project Datasets Algorithm Data Science 52

ProjectPro

AUGUST 2, 2021

Humans, the truly visual beings we are, respond to and process visual data better than any other data type. The human brain is said to process images 60,000 times faster than text. This process has developed and augmented popular platforms and libraries like MATLAB, scikit-image, and OpenCV.

Coding 40

Coding Python Process Project 40

Knowledge Hut

JANUARY 12, 2024

It is used as a pre-processing step in Machine Learning and applications of pattern classification. The main agenda is to remove the redundant and dependent features by changing the dataset onto a lower-dimensional space. variables) in a particular dataset while retaining most of the data.

Machine Learning 97

Machine Learning Datasets Medical Algorithm 97

Snowflake

SEPTEMBER 14, 2023

The advent of advanced AI tools, including LLMs and generative AI Large language models (LLMs) and natural language processing (NLP) are changing everything. To learn more about the modern marketing data stack and get more value from your data, download the full report here.

Media 87

Media Technology Datasets Data 87

Cloudera

FEBRUARY 1, 2022

However, because we are only interested in comparing snowflakes, we need to bring our own dataset consisting solely of snowflakes, and a lot of them. It turns out that there aren’t very many publicly available datasets of snowflake images. app/frontend/build/assets/semsearch/datasets/iconic200/”. Notebook Section 1.

Deep Learning 109

Deep Learning Datasets Coding Machine Learning 109

Knowledge Hut

OCTOBER 27, 2023

On an unclean and disorganised dataset, it is impossible to build an effective and solid model. When cleaning the data, it can take endless hours of study to find the purpose of each column in the dataset. Reddit datasets. The project is written in R, and it makes use of the Janeausten R package's dataset.

Data Science 96

Data Science Coding Project Datasets 96

Confluent

FEBRUARY 21, 2019

By taking data from a tool such as Sysmon and streaming it into Kafka for processing in KSQL, you can rapidly detect suspicious behavior by looking for a process spawning a new process that makes an external network connection. This is because the Create method allows a user to create a process either locally or remotely.

Process 80

Process Kafka Datasets SQL 80

Knowledge Hut

OCTOBER 30, 2023

Deep learning projects are applications or systems that use deep learning algorithms to perform complex tasks such as image recognition, natural language processing, speech recognition, and prediction. This dataset contains medical record data for Pima Indians and indicates whether they had an onset of diabetes within five years.

Deep Learning 52

Deep Learning Project Datasets Machine Learning 52

FreshBI

JANUARY 16, 2024

“ To make this process simpler and faster, you can use Power Custom Visuals instead. ” Stuffed: at $9022.50” Here the prompt directs ChatGPT to derive insights from the dataset provided. The code then repeats the process for the previous year. As of the date of writing this blog, there’s no direct way to link the two.

BI 52

BI Business Intelligence Datasets Coding 52

Towards Data Science

JANUARY 7, 2024

It’s crucial to not only process the data but also ensure its quality. Data profiling gives us statistics about different columns in our dataset. GitHub - sarthak-sarbahi/whylogs-pyspark Start by downloading the sample data (CSV) from here. Now, let’s get to know the dataset we’ll be working with. So let’s dive in!

Data Pipeline 80

Data Pipeline Hospitality Data Validation Datasets 80

Towards Data Science

MARCH 6, 2023

And, like in lego, the complexity of the building process is determined by the complexity of the final goal. The tools Spark is an all-purpose distributed memory-based data processing framework geared towards processing extremely large amounts of data. Create a new dataset in Google Big Query named censo-ensino-superior 5.

Google Cloud 84

Google Cloud Cloud Storage Data Pipeline Cloud 84

ProjectPro

FEBRUARY 28, 2022

It all began with processing images to detect objects, which later escalated to face detection and facial expression recognition. The efficiency of recognition relies on the process of feature extraction. Before we jump on to the code, allow us to give you a fair idea of the dataset. Can we really do that? The answer is YES!

Coding 52

Coding Project Deep Learning Datasets 52

Knowledge Hut

DECEMBER 22, 2023

Some offer great productivity and performance to process significant amounts of data, making them better suitable for data science. Learn how to work with big data technologies to process and analyze large datasets. Emphasize analytical thinking and clear communication of your thought process.

Portfolio 98

Portfolio Data Science Programming Language Scala 98