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 76

Datasets Metadata Bytes Machine Learning 76

Knowledge Hut

OCTOBER 29, 2023

Source Code: Hospital Management System 2. Source Code: Weather Forecast App 3. Once you have a dataset, you will need to process it and transform it into a format that can be displayed in your app. Source Code: News Feed App 4. Source Code: OCR System 5. Source Code: Library Management System 6.

Computer Science 111

Computer Science Coding Project Hospitality 111

Tweag

SEPTEMBER 23, 2024

As we were developping FawltyDeps 1 , a tool to ensure that declared dependencies match the actual imports in the code, we had to accommodate many of these ways. Data First, we need to collect the names and source code locations of projects that we want to include in the analysis. Now, where did we find these projects?

Python 56

Python Project Metadata Datasets 56

ProjectPro

SEPTEMBER 27, 2021

The training dataset is ready and made available for you for most of these beginner-level object detection projects. You can use the flowers recognition dataset on Kaggle to build this model. The flowers recognition dataset consists of multiple pictures with different types of flowers. Make predictions on the test set.

Coding 52

Coding Project Datasets Retail 52

ProjectPro

FEBRUARY 5, 2021

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. Table of Contents What is the MNIST dataset? Test the Trained Neural Network Visualizing the Test Results Ending Notes What is the MNIST dataset?

Datasets 40

Datasets Deep Learning Medical Algorithm 40

Knowledge Hut

OCTOBER 26, 2023

This project will help you learn how to choose a CMS and deploy a website without writing its code from scratch. Source code: GitHub 2. Source Code: Mass Emailing 3. Source Code: GitHub 4. Source Code: GitHub 5. Source code: GitHub 2. Amazon S3 and EC2 instances can also be used to host a website.

AWS 52

AWS Coding Project Cloud Computing 52

Cloudyard

OCTOBER 1, 2024

Read Time: 3 Minute, 57 Second Pandas, a popular Python library, is a fantastic tool for small to moderately sized data, but it struggles with large-scale datasets. This will also presents how Snowpark solves challenges that Pandas faces with large datasets. We have considered the dataset of 150M data.

Datasets 52

Datasets Big Data Data Warehouse Cloud 52

ProjectPro

AUGUST 24, 2021

Explore different types of Data Formats: A data engineer works with various dataset formats like.csv,josn,xlx, etc. They are also often expected to prepare their dataset by web scraping with the help of various APIs. Machine Learning web service to host forecasting code.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Knowledge Hut

FEBRUARY 29, 2024

Then, based on this information from the sample, defect or abnormality the rate for whole dataset is considered. Hypothesis testing is a part of inferential statistics which uses data from a sample to analyze results about whole dataset or population. While using Amazon SageMaker datasets are quick to access and load.

Data Science 98

Data Science Datasets Machine Learning Database Design 98

ProjectPro

AUGUST 30, 2022

Top 5 Loan Prediction Datasets to Practice Loan Prediction Projects Univ.AI Top 5 Loan Prediction Datasets to Practice Loan Prediction Projects Univ.AI Let's look at some of these datasets. Top 5 Loan Prediction Datasets to Practice Loan Prediction Projects 1. Loan Prediction Dataset Based on Customer Behavior This Univ.AI

Machine Learning 52

Machine Learning Coding Project Datasets 52

Knowledge Hut

FEBRUARY 29, 2024

Anaconda Navigator Anaconda Navigator is a UI Interface, as shown above, which allows you to access different tools like Jupyter Notebook, VS Code, and Spyder directly by clicking on the launching button. We are installing it for MacOSx, but you can also go for the same steps by downloading Anaconda Navigator for Windows.

Data Science 52

Data Science Project Datasets Python 52

Knowledge Hut

JANUARY 3, 2024

Importing And Cleaning Data This is an important step as a perfect and clean dataset is required for distinct and perfect data visualization. Pros And Cons Highest level of control for the rapid creation of charts Many graphs with fewer codes and higher resolution No pre-set defaults, and users have to define them each time.

Python 98

Python Programming Language Datasets R (Programming) 98

ProjectPro

AUGUST 16, 2021

Please don’t think twice about scrolling down if you are looking for data mining projects ideas with source code. FAQs on Data Mining Projects 15 Top Data Mining Projects Ideas Data Mining involves understanding the given dataset thoroughly and concluding insightful inferences from it.

Data Mining 40

Data Mining Coding Project Datasets 40

Towards Data Science

NOVEMBER 16, 2023

Splittable in chunks : instead of processing an entire dataset in a single, resource-intensive operation, batch data can be divided into smaller, more manageable segments. You can find the complete code to implement this scenario in the VDK GitHub repository. Please note that you need a free API key to download data from Europeana.

Data Process 73

Data Process Process Raw Data Data 73

ProjectPro

AUGUST 21, 2021

This project, although simple, is intended entirely towards understanding the various features available and configurable using the matplotlib library for a simple scatter plot, which is generally used to observe the relations between two attributes in the dataset. NOTE: The plots generated here are, however, Matplotlib objects.

Coding 52

Coding Project Datasets Machine Learning 52

DareData

JUNE 11, 2024

Although we’ll use a simple dataset here (making it accessible for anyone to run this code on their computer), the principles we’ll see can be applied to other image classification algorithms. data', train=True, download=True, transform=transform) test_dataset = torchvision.datasets.MNIST(root='./data', Let’s start!

Algorithm 52

Algorithm Datasets Deep Learning Architecture 52

Cloudera

FEBRUARY 1, 2022

AMPs are developed by ML research engineers at Cloudera’s Fast Forward Labs , and as a result they are a great source for ML best practices and code snippets. For the most part, we will be able to reuse parts of the existing code. It turns out that there aren’t very many publicly available datasets of snowflake images.

Deep Learning 109

Deep Learning Datasets Coding Machine Learning 109

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. In this example, we will use a Jupyter Notebook session to run our code. Get the Dataset. pip install -r requirements.txt.

Machine Learning 136

Machine Learning Datasets Data Science Raw Data 136

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

Snowflake

APRIL 24, 2024

Efficiently Intelligent: Arctic excels at enterprise tasks such as SQL generation, coding and instruction following benchmarks even when compared to open source models trained with significantly higher compute budgets. license provides ungated access to weights and code. Arctic is efficiently intelligent and truly open.

Amazon Web Services 145

Amazon Web Services SQL AWS Architecture 145

Towards Data Science

JANUARY 26, 2023

Direct Download from Amazon S3 In this post, we will assume that we are downloading files directly from Amazon S3. For this and all subsequent code snippets, we assume that your AWS account and local environment have been appropriately configured to access Amazon S3. client('s3') s3.upload_file('2GB.bin',

Cloud Storage 70

Cloud Storage Big Data Cloud AWS 70

Christophe Blefari

SEPTEMBER 13, 2024

The articles contains a lot of code snippets to understand what's under the hood. Daily cache implementation in Python — A highly effective approach for caching when working with large datasets stored in distant buckets is to implement a local cache. It avoids the need to repeatedly download the data.

Pipeline-centric 100

Pipeline-centric Data Python Data Science 100

Knowledge Hut

OCTOBER 30, 2023

Top Deep Learning Projects with Source Code ( Beginner and Final Year Students) Looking for inspiration for your deep learning projects for the final year with source code? Continue to read this blog, where you can find a variety of deep learning projects with accompanying source code to get you started!

Deep Learning 52

Deep Learning Project Datasets Machine Learning 52

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. The previous version used only about 3.5k First we pull out the relevant columns from the raw data file.

AWS 59

AWS Building Python Bytes 59

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

ProjectPro

AUGUST 2, 2021

Upskill yourself for your dream job with industry-level big data projects with source code 2) Image Smoothing Image smoothing ameliorates the effect of high-frequency spatial noise from an image. You can try to replicate the results by using this Kaggle dataset ImageProcessing.

Coding 40

Coding Python Process Project 40

Marc Lamberti

NOVEMBER 23, 2022

It operates entirely in memory leading to out-of-memory errors if the dataset is too big. We are going to perform data analysis on the Stock Market dataset. This dataset contains CSV and JSON files for all NASDAQ, S&P500, and NYSE-listed companies. It’s a 10.22GB uncompressed dataset, and 1.0GB zip compressed.

Datasets 130

Datasets Python SQL Database 130

Towards Data Science

JANUARY 7, 2024

Data profiling gives us statistics about different columns in our dataset. Table of contents Components of whylogs Environment setup Understanding the dataset Getting started with PySpark Data profiling with whylogs Data validation with whylogs Components of whylogs Let’s begin by understanding the important characteristics of whylogs.

Data Pipeline 75

Data Pipeline Hospitality Data Validation Datasets 75

Edureka

JULY 5, 2024

Drag-and-drop interface: The intuitive interface allows complex data preparation tasks without needing to write SQL code, simplifying the workflow significantly. Tableau Prep Builder Download and Installation To download and install Tableau Prep Online, you’ll need a Creator product key and the installer.

Data Preparation 40

Data Preparation Process BI ETL Tools 40

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

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. For that matter, we’ll take a look at the adolescent tobacco study example , used in the paper. Image by Author.

Datasets 101

Datasets Machine Learning Data Data Science 101

Towards Data Science

JULY 8, 2024

Tensorflow Transform helps us achieve it in a distributed environment over a huge dataset. This dataset is free to use for commercial and non-commercial purposes. A description of the dataset is shown in the below figure. To explore these artifacts programatically, use the below code. You can access it from here.

Data Preparation 46

Data Preparation Datasets Metadata Data Ingestion 46

FreshBI

JANUARY 16, 2024

Stuffed: at $9022.50” Here the prompt directs ChatGPT to derive insights from the dataset provided. In this case, we clicked on the 2023 button, and the prompt (the dataset, to be more specific) changed accordingly: Because there’s a change in input, there’s a different response, too. In 2021, our top sellers were Plain: at $2,768.00

BI 52

BI Business Intelligence Datasets Coding 52

Scott Logic

OCTOBER 18, 2023

To run JavaScript code, the runtime is compiled to WebAssembly, with your code running within the WebAssembly-hosted interpreter. If you want to explore the data, feel free to download the dataset , please do attribute if you reproduce or use this data.

Programming Language 145

Programming Language Coding Java Programming 145

Towards Data Science

MARCH 6, 2023

The implementation The pipeline idea is simple, download the CSV files to the local machine, convert them into a Delta-Lake table stored in a GCS bucket, do the transformations needed over this delta table, and save the results in a Big Query Table that can be easily consumed by other downstream tasks. in CSV files (one per year).

Google Cloud 79

Google Cloud Cloud Storage Data Pipeline Cloud 79

Edureka

MAY 31, 2024

MIDJourney AI GitHub Copilot Alpha code What is Generative AI? Generative AI works by learning patterns and structures from a dataset and then using that knowledge to produce new content that resembles the data it was trained on. You can provide Prompts with various inputs, such as text, images, videos, or even code.

Education 95

Education Algorithm Coding Deep Learning 95

Knowledge Hut

OCTOBER 29, 2023

Refer to the architecture diagram below: For the scope of this project, we will consider a simple dataset and use the Azure Anomaly Detector API to detect any outliers present in it. To build the project: Download the dataset and keep it ready for use. Refer the code from here and follow the document to visualize the results.

Project 52

Project Hospitality Food Datasets 52