ProjectPro

JUNE 6, 2025

Movement and ease of access to data are essential to generating any form of insight or business value. Non-technical users will benefit from self-service analytics because it will make it easier to access information fast. IT professionals are often disappointed by the time spent preparing data for loading.

Data Warehouse 40

Data Warehouse Coding Project Google Cloud 40

ProjectPro

JUNE 6, 2025

Pre-trained models are models trained on an existing dataset. Cat vs. Dog Image Classification System If you are a beginner in deep learning, this is a project you should start with.First, you will need to find a labeled dataset of cat and dog images. You can find an existing dataset of labeled faces on the Internet.

Deep Learning 59

Deep Learning Coding Project Portfolio 59

Engineering at Meta

JANUARY 22, 2025

In order to build high-quality data lineage, we developed different techniques to collect data flow signals across different technology stacks: static code analysis for different languages, runtime instrumentation, and input and output data matching, etc. Static analysis tools simulate code execution to map out data flows within our systems.

Data Warehouse 116

Data Warehouse SQL Programming Language Data 116

Netflix Tech

NOVEMBER 12, 2024

However, this category requires near-immediate access to the current count at low latencies, all while keeping infrastructure costs to a minimum. The Counter Abstraction API resembles Java’s AtomicInteger interface: AddCount/AddAndGetCount : Adjusts the count for the specified counter by the given delta value within a dataset.

Datasets 103

Datasets Computer Science Kafka Systems 103

ProjectPro

JUNE 6, 2025

Project Idea: You can use the Resume Dataset available on Kaggle to build this model. This dataset contains only two columns - job title and the candidate’s resume information. Tools and Libraries: Python, NLTK Dataset: Kaggle Resume Dataset Experience Hands-on Learning with the Best Course for MLOps 2.

Project 98

Project Datasets Deep Learning Machine Learning 98

ProjectPro

JUNE 6, 2025

Feature Store : Feature stores are used to store variations on the feature set leveraged for machine learning models t hat multiple teams can access. Just one line of code will enable you to quickly perform the initial EDA in a visually appealing and shareable format. The source code for inspiration can be found here.

Project 66

Project Amazon Web Services Machine Learning Data Science 66

ProjectPro

JUNE 6, 2025

With AWS DevOps, data scientists and engineers can access a vast range of resources to help them build and deploy complex data processing pipelines, machine learning models, and more. Suppose you want to learn to use AWS CloudFormation, a tool for defining and deploying infrastructure resources as code.

AWS 61

AWS Project Medical Deep Learning 61

ProjectPro

JUNE 6, 2025

Real-World End-to-End Data Engineering Project with Source Code to Build Azure Data Factory Pipeline Step 1 - Define the Data Sources to Create Azure Data Factory Pipeline In this step, we will identify the data sources (e.g., machines, sensors) from which data needs to be extracted and loaded into a centralized data warehouse.

Coding 40

Coding Manufacturing Data Cleanse Data Warehouse 40

ProjectPro

JUNE 6, 2025

When Glue receives a trigger, it collects the data, transforms it using code that Glue generates automatically, and then loads it into Amazon S3 or Amazon Redshift. You can produce code, discover the data schema, and modify it. For analyzing huge datasets, they want to employ familiar Python primitive types.

AWS 66

AWS Scala Metadata Data Lake 66

ProjectPro

JUNE 6, 2025

Source Code: E-commerce product reviews - Pairwise ranking and sentiment analysis. Source Code: Chatbot example application using python - text classification using nltk. Source Code: Topic Modeling using K Means Clustering. Fine-tuning models on custom datasets improves accuracy for specific applications.

Coding 49

Coding Project Building Medical 49

ProjectPro

JUNE 6, 2025

The first step in a machine learning project is to explore the dataset through statistical analysis. However, with large datasets, these tasks have to be automated. With time, one is likely to witness changes in the input dataset, which must be reflected in the output. you have used in your project.

Amazon Web Services 68

Amazon Web Services Machine Learning Datasets Algorithm 68

The Pragmatic Engineer

OCTOBER 17, 2024

The startup was able to start operations thanks to getting access to an EU grant called NGI Search grant. The historical dataset is over 20M records at the time of writing! They use GitHub Actions and Pulumi templates to kick off benchmark tasks: that plumbing code to start benchmarking can be found in the sc-runner repo.

Cloud 326

Cloud Metadata AWS Cloud Computing 326

ProjectPro

JUNE 6, 2025

Click here to view a list of 50+ solved, end-to-end Big Data and Machine Learning Project Solutions (reusable code + videos) PyTorch 1.8 has introduced better features for code optimization, compilation, and front-ned apis for scientific computing. vs Tensorflow 2.x x in 2021 What's New in TensorFlow 2.x

Deep Learning 97

Deep Learning Machine Learning Programming Language Python 97

ProjectPro

JUNE 6, 2025

As different sets of text (or corpus ) are vital in computational linguistics, NLTK also gives access to many of these sets, models, and pre-trained utilities. NLTK gives access to a pretty good pre trained lemmatizer called the WordNetLemmatizer. We will use the movie reviews dataset from NLTK.

Building 66

Building Datasets Python Algorithm 66

ProjectPro

JUNE 6, 2025

With the global data volume projected to surge from 120 zettabytes in 2023 to 181 zettabytes by 2025, PySpark's popularity is soaring as it is an essential tool for efficient large scale data processing and analyzing vast datasets. Some of the major advantages of using PySpark are- Writing code for parallel processing is effortless.

Hadoop 68

Hadoop Metadata Java Datasets 68

ProjectPro

JUNE 6, 2025

Python Flask Project Ideas for Beginners with Source Code If you are a beginner looking for Python projects using Flask, check out these interesting Python Flask projects with source code. So, get ready to build exciting Flask-based projects and take your data science and machine learning skills to the next level!

Data Science 69

Data Science Python Project Google Cloud 69

ProjectPro

JUNE 6, 2025

And, with largers datasets come better solutions. Use Athena in AWS to perform big data analysis on massively voluminous datasets without worrying about the underlying infrastructure or the cost associated with that infrastructure. Redshift Amazon Athena Amazon Redshift A serverless tool for building and querying large datasets.

AWS 67

AWS SQL Big Data Raw Data 67

ProjectPro

JUNE 6, 2025

Built on datasets that fail to capture the majority of a company's data, these models are doomed to return inaccurate results. This helps data scientists and business analysts access and analyze all the data at their disposal. Master data analytics skills with unique big data analytics mini projects with source code.

Data Lake 63

Data Lake Data Warehouse Metadata Unstructured Data 63

ProjectPro

JUNE 6, 2025

Each dataset has a separate pipeline, which you can analyze simultaneously. To assess how the model works against new datasets, you need to divide the existing labeled data into training, testing, and validation data subsets at this point. DVC handles large files, data sets, machine learning models, metrics, and code.

Machine Learning 58

Machine Learning Building Amazon Web Services Deep Learning 58

Netflix Tech

DECEMBER 17, 2024

Metric definitions are often scattered across various databases, documentation sites, and code repositories, making it difficult for analysts and data scientists to find reliable information quickly. Enter DataJunction (DJ). For example, LORE provides human-readable reasoning on how it arrived at the answer that users can cross-verify.

Engineering 88

Engineering Entertainment Amazon Web Services Utilities 88

ProjectPro

JUNE 6, 2025

The No-Code orchestration offered by Data Factory makes it an effective tool for any data engineer. Code-Free Transformation: UI-driven mapping dataflows. Ability to run Code on Any Azure Compute: Hands-on data transformations Ability to rehost on-prem services on Azure Cloud in 3 Steps: Many SSIS packages run on Azure cloud.

Data Lake 60

Data Lake Metadata SQL Datasets 60

Snowflake

MARCH 31, 2025

For image data, running distributed PyTorch on Snowflake ML also with standard settings resulted in over 10x faster processing for a 50,000-image dataset when compared to the same managed Spark solution. Secure access to open source repositories via pip and the ability to bring in any model from hubs such as Hugging Face (see example here ).

Healthcare 96

Healthcare Medical Government Food 96

Engineering at Meta

APRIL 28, 2025

We developed tools and APIs for developers to organize assets, classify data, and auto-generate annotation code. Each product features its own distinct data model, physical schema, query language, and access patterns. Datasets provide a native API for creating data pipelines.

Metadata 83

Metadata Data Utilities Data Warehouse 83

Precisely

APRIL 7, 2025

After my (admittedly lengthy) explanation of what I do as the EVP and GM of our Enrich business, she summarized it in a very succinct, but new way: “Oh, you manage the appending datasets.” Matching accuracy: Matching records between datasets is complex. ” That got me thinking.

Retail 75

Retail Datasets Data Telecommunication 75

ProjectPro

JUNE 6, 2025

Spark uses Resilient Distributed Dataset (RDD), which allows it to keep data in memory transparently and read/write it to disc only when necessary. It can also access structured and unstructured data from various sources. Analysis and Visualization on Yelp Dataset Explore more Apache Spark Data Engineering Projects here.

Data Engineer 45

Data Engineer Data Engineering Engineering Kafka 45

ProjectPro

JUNE 6, 2025

FAQs on Data Engineering Projects Top 30+ Data Engineering Project Ideas for Beginners with Source Code [2025] We recommend over 20 top data engineering project ideas with an easily understandable architectural workflow covering most industry-required data engineer skills. Build your Data Engineer Portfolio with ProjectPro!

Data Engineer 59

Data Engineer Data Engineering Project Engineering 59

ProjectPro

JUNE 6, 2025

There are three types of padding: Get FREE Access to Machine Learning Example Codes for Data Cleaning, Data Munging, and Data Visualization Valid Padding - In this case, the last convolution is dropped/skipped if the filter is falling outside the input matrix. Access the Dogs vs Cats to start working on this project.

Architecture 90

Architecture Deep Learning Banking Datasets 90

Snowflake

FEBRUARY 12, 2025

Agents need to access an organization's ever-growing structured and unstructured data to be effective and reliable. As data connections expand, managing access controls and efficiently retrieving accurate informationwhile maintaining strict privacy protocolsbecomes increasingly complex. text, audio) and structured (e.g.,

Unstructured Data 92

Unstructured Data Government SQL Structured Data 92

ProjectPro

JUNE 6, 2025

By extracting features from the images through a deep learning model like MobileNetV, you can use the KNN algorithm to display the images from an open-source dataset similar to your image. The pyzbar library has a decode function that locates and extracts information from Barcodes and QR codes in an image.

Project 66

Project Deep Learning Datasets Algorithm 66

ProjectPro

JUNE 6, 2025

For example, consider the Australian Wine Sales dataset containing information about the number of wines Australian winemakers sold every month for 1980-1995. Get FREE Access to Machine Learning Example Codes for Data Cleaning, Data Munging, and Data Visualization An Autoregressive (AR) Process Let E t denote the variable of interest.

Deep Learning 66

Deep Learning Machine Learning Python Datasets 66

ProjectPro

JUNE 6, 2025

The AI platform can be used for several use cases like access control, number plate recognition, recommendation system, business analytics with NLP, etc. CodeCommit maintains code consistency by enabling you to store your sample code in one or more repositories.

Project 45

Project AWS Algorithm Machine Learning 45

ProjectPro

JUNE 6, 2025

In traditional machine learning, models are trained from scratch on specific datasets, requiring large amounts of labeled data and computational resources. Traditionally, you would start from scratch, collecting a large dataset of animal images and training a model to recognize these animals.

Deep Learning 52

Deep Learning Project Datasets Machine Learning 52

ProjectPro

JUNE 6, 2025

AWS Lambda will fetch real-time personalization scores, and Amazon DynamoDB will serve as a fast-access data layer. This dataset, containing over 200K product reviews from customers across five countries between 1995 and 2015, is a valuable asset for machine learning and natural language processing applications.

AWS 60

AWS Project Food Cloud Computing 60

ProjectPro

JUNE 6, 2025

k-Nearest Neighbors (k-NN) This algorithm is simple and effective for smaller datasets, classifying emotions based on the majority class among the k-nearest neighbors. So without any further ado, we present you a functional code for a speech-emotion recognition project in Python. For now, we use it just to load into a NumPy array.

Machine Learning 66

Machine Learning Project Datasets Algorithm 66

ProjectPro

JUNE 6, 2025

When any particular project is open-sourced, it makes the source code accessible to anyone. Multi-node, multi-GPU deployments are also supported by RAPIDS, allowing for substantially faster processing and training on much bigger datasets. Anyone can freely use, study, modify and improve the project, enhancing it for good.

Big Data 49

Big Data Project Metadata Programming Language 49

ProjectPro

JUNE 6, 2025

This would allow the customer service team to quickly and easily access the prediction without going through a cumbersome process of manually inputting the data and running the model. Deploy The API: Finally, deploy the API using a platform such as Heroku or AWS to make it accessible to users. Why Practice FastAPI Projects?

Project 45

Project MongoDB Machine Learning AWS 45

ProjectPro

JUNE 6, 2025

This blog covers all the steps to master data preparation with machine learning datasets. In building machine learning projects , the basics involve preparing datasets. This is because the raw data usually has various inconsistencies that must be resolved before the dataset can be fed to machine learning/ deep learning algorithms.

Data Preparation 45

Data Preparation Machine Learning Project IT 45