Knowledge Hut

JANUARY 18, 2024

Its popularity has expanded over time, and individuals have begun to use diverse data science approaches to develop their businesses and boost consumer happiness. To extract the data, they use algorithms and prediction models to retrieve the data required by the business and aid in data evaluation. Why Data Science?

Data Science 98

Data Science R (Programming) Computer Science Algorithm 98

Christophe Blefari

JULY 8, 2023

( credits ) Hey you, this is the Saturday Data News edition 🥲 Time flies. I'm working for the Series of articles in advance for August about "creating data platforms" and I'm looking for ideas about the data I could use for this. Having some kind of simulated real-time data would be the best.

Kafka 130

Kafka PostgreSQL Transportation Data 130

Tweag

APRIL 3, 2023

Using a monorepo is an excellent way to do that. This makes it easy to use the same code style and documentation standards. Uniformity smooths the onboarding of newcomers as well as the reassignment of engineers to different internal projects. a sandbox), with a Python interpreter and the right Python dependencies (packages).

Python 98

Python Coding Project Data Science 98

Christophe Blefari

SEPTEMBER 28, 2023

But every time I went to a conference in the past, I came back with ideas to change everything because someone introduced me to a new fancy stuff. The modern data stack has always been nice words to bundle a philosophy used to build data platform. All over the world, people gather in huge venues to attend conferences. Cloud-first.

Cloud Storage 147

Cloud Storage Big Data Hadoop SQL 147

Towards Data Science

FEBRUARY 18, 2024

How to Stream and Apply Real-Time Prediction Models on High-Throughput Time-Series Data Photo by JJ Ying on Unsplash Most of the stream processing libraries are not python friendly while the majority of machine learning and data mining libraries are python based. An event is generated by a producer (e.g.

Kafka 79

Kafka Python Process Google Cloud 79

Maxime Beauchemin

APRIL 26, 2023

It’s time for me to put on my helmet, secure it with duct tape, and contribute something that can help propel this frenzy forward ??? To support engineers in this process, I am introducing Promptimize , a Python toolkit designed to measure success and outcomes while doing prompt engineering. What a stellar assistant!

SQL 148

SQL Database Engineering Software Engineer 148

LinkedIn Engineering

OCTOBER 19, 2023

This robust framework empowers near real-time data processing for critical services and platforms, ranging from machine learning and notifications to anti-abuse AI modeling. In 2010, they introduced Apache Kafka , a pivotal Big Data ingestion backbone for LinkedIn’s real-time infrastructure.

Process 119

Process Lambda Architecture Kafka Machine Learning 119

Tweag

MAY 1, 2024

Nixpkgs and NixOS still need more time. A lot has happened during that time, so this text is quite lengthy. The details of this report will mainly be interesting to power users and active contributors, or people working on software projects that are in a similar situation as Nix. And that time was needed.

Architecture 95

Architecture Project Coding Designing 95

Knowledge Hut

MAY 3, 2024

It was originally developed by Adobe and is a file format used to present and transfer documents easily and reliably. It uses the file extension.pdf. In fact, PDF is the most widely used digital media, which is now considered an open standard maintained by the International Standards Organization (ISO).

Python 52

Python Digital Media Coding Programming 52

Data Engineering Podcast

MARCH 13, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. When is Acceldata the wrong choice?

Data Lake 100

Data Lake Relational Database Data Data Engineering 100

Knowledge Hut

FEBRUARY 29, 2024

In this century, as Technology is growing, so is Data, and to use it, we need to understand the pattern and the science of it, and so is Data Science , one of the fastest and most crucial techs every product and organization needs. It is easy to use. It helps you to maintain production-ready projects. conda install matplotlib 2.

Data Science 52

Data Science Project Datasets Python 52

ProjectPro

FEBRUARY 5, 2022

This blog introduces the concept of time series forecasting models in the most detailed form. Next, you will find a section that presents the definition of a time series forecasting article. After that, you will explore popular time-series-forecasting models. How do you do a time series analysis?

Deep Learning 52

Deep Learning Datasets Python Machine Learning 52

Knowledge Hut

OCTOBER 27, 2023

Whether you are a student or a working professional, the journey to be an industry-ready Data Scientist would never be fulfilled unless there is a good portfolio of projects considerably demonstrated in the resume. Choosing the right project is crucial as it could set you apart from the other Data Scientists. to detect anomalies.

Data Science 52

Data Science Python Project Manufacturing 52

Knowledge Hut

JANUARY 29, 2024

At the same time, Cloud Computing allows the data to be easily analyzed by the data scientists. With the help of Cloud Computing Classes , candidates can learn more about cloud computing while gaining certification at the same time. Microsoft Azure , Amazon Web Series , IBM, Google, and others are examples of CSP.

Cloud Computing 98

Cloud Computing Data Science Cloud Amazon Web Services 98

Data Engineering Podcast

JUNE 19, 2022

Announcements Hello and welcome to the Data Engineering Podcast, the show about modern data management When you’re ready to build your next pipeline, or want to test out the projects you hear about on the show, you’ll need somewhere to deploy it, so check out our friends at Linode. When is Canvas the wrong choice?

Metadata 130

Metadata Unstructured Data MongoDB MySQL 130

Data Engineering Weekly

MARCH 24, 2024

Companies are more open to adopting Gen AI for their internal use cases but have reservations about rolling it out to their clients. MES framework evaluates model quality across various lifecycle stages—prototyping, training, deployment, and prediction—using Service Level Agreement (SLA) principles.

Data Engineering 62

Data Engineering Data Engineer Engineering Metadata 62

Cloudera

JULY 27, 2021

Only through hands-on experimentation can we discern truly useful new algorithmic capabilities from hype. AMPs accelerate machine learning projects and kickstart AI use cases by providing example workflows and applications that leverage the power of the platform. Not every project requires a fully custom web app.

Data Science 114

Data Science Machine Learning Deep Learning Python 114

Knowledge Hut

SEPTEMBER 6, 2023

In this article, I’ve compiled the list of the best Data Science Certificate Programs, which will help you hone your skills and acquire knowledge on the most used techniques of data science. The below described Data Science Bootcamp courses elaborates different concepts of data science thoroughly with relevant case studies and examples.

Data Science 97

Data Science Certification Business Analyst Machine Learning 97

Tweag

MAY 24, 2023

These are all “good things” for building robust software, which inevitably lead us to using languages such as Haskell, OCaml and Rust. However, it would be remiss of us to snub languages that don’t enforce the same disciplines, but are nonetheless popular choices in industry. So let’s look at what we can do in Python.

Python 105

Python Programming Language Programming Coding 105

Engineering at Meta

MAY 16, 2023

The project has delivered significant benefits to the MySQL deployment at Meta, including higher reliability, provable safety, significant improvements in failover time, and operational simplicity — all with equal or comparable write performance. For this, we used the well-understood consensus protocol Raft.

MySQL 136

MySQL Building Engineering Database 136

Knowledge Hut

OCTOBER 24, 2023

The present article will discuss in detail the importance of data visualization, tools, use cases and various data visualization project ideas for different levels of participants. What Is Data Visualization Project? We will mention some more sample data visualization projects later on in this article.

Project 52

Project BI Datasets Big Data 52

Data Engineering Weekly

JULY 2, 2023

Though the system not supporting any LinkedIn production ecosystem, it is an exciting open source project to watch. Can't we use the vector feature in the existing databases? Similarly, the blog narrates how to use vector searching in Postgres using PGVector. Should you?

Data Engineering 52

Data Engineering Data Engineer Engineering Pipeline-centric 52

Knowledge Hut

FEBRUARY 1, 2024

Every time someone uses the internet, more data is added. We need assistance from various Data Science methodologies to make sense of this enormous amount of data and use it for the company's objectives, etc. E-commerce is one industry that most uses data science and machine learning techniques.

Data Science 96

Data Science Retail Algorithm Manufacturing 96

Knowledge Hut

JANUARY 19, 2024

In data science, we use various tools, processes, and algorithms to extract insights from structured and unstructured data. Programming Languages Delving into programming languages such as R and Python, along with exposure to database languages like SQL. Allowing machines to make decisions using visuals.

Data Science 52

Data Science Machine Learning Datasets Algorithm 52

Tweag

JULY 12, 2023

That is why we want to build systems that foster cross-team communication, and using a monorepo is an excellent way to do that. In our previous article , we described our choice of structure and tools to bootstrap a Python monorepo. We made a GitHub template which you can use to bootstrap your own monorepo.

Python 52

Python Coding Systems Designing 52

Snowflake

JANUARY 4, 2024

But you’ll likely need to spend time and effort to acquire, vet and transform external data into a useful resource that delivers clear ROI. Cybersyn embraced Snowflake Native Apps from the start, seeing their usefulness as a way to give customers direct access to not just data, but logic and functions around the data.

SQL 98

SQL Retail Data Government 98

Knowledge Hut

JUNE 16, 2023

Python is a highly versatile and popular programming language that is being used in a wide range of industries, including software development, data science, machine learning, web development, and scientific research. Python can build various data visualizations and has several libraries that let coders write programs.

Python 52

Python Project Programming Language Programming 52

ProjectPro

JANUARY 27, 2023

Join us as we highlight some of the most popular data science applications in finance and exciting project ideas for financial data scientists to help them stay ahead of the curve. As data science evolves, let’s explore the top 7 use cases of data science in finance that help financial companies thrive and boost their revenue.

Finance 52

Finance Data Science Unstructured Data Algorithm 52

Towards Data Science

JUNE 27, 2023

Performance, Speed, and Memory-Efficiency As we all know, pandas was built using numpy, which was not intentionally designed as a backend for dataframe libraries. Essentially, Arrow is a standardized in-memory columnar data format with available libraries for several programming languages (C, C++, R, Python, among others).

Pipeline-centric 98

Pipeline-centric Data Science Machine Learning Datasets 98

Ascend.io

FEBRUARY 23, 2024

Exciting, isn’t it Yet, embarking on the AI adoption journey introduces a series of challenges, with one of the most significant being the readiness of your data platform. What capabilities should your data platform have to not only support but also elevate your AI projects? How do you know if you are technically ready for AI?

Cloud Storage 52

Cloud Storage Data Ingestion Machine Learning Algorithm 52

dbt Developer Hub

OCTOBER 17, 2022

For years working in data and analytics engineering roles, I treasured the daily camaraderie sharing a small office space with talented folks using a range of tools - from analysts using SQL and Excel to data scientists working in Python. ❌ Don’t : Use Python where the solution in SQL is just as direct. .

SQL 52

SQL Python Programming Language Data Analysis 52

ProjectPro

JULY 10, 2021

Time series analysis and forecasting is a dark horse in the domain of Data Science. Time series is among the most applied Data Science techniques in various industrial and business operations, such as financial analysis , production planning, supply chain management, and many more. What is Time Series Analysis ?

Project 40

Project Banking Datasets Python 40

Knowledge Hut

APRIL 26, 2024

Machine Learning is a sub-branch of Artificial Intelligence, used for the analysis of data. It has found tremendous use in sectors across industries, with its ability to solve complex problems which humans are not able to solve using traditional techniques. There is no end to what can be achieved with the right ML algorithm.

Machine Learning 98

Machine Learning Algorithm Deep Learning Programming Language 98

DareData

NOVEMBER 28, 2023

Learn about Tensors and how to use them in one of the most famous machine learning libraries, PyTorch One of most important libraries in the Deep Learning firld (and inclusively, where ChatGPT was built upon) is pytorch. With this small introduction on mathematical concepts, let’s explore how to use pytorch ‘s in Python!

Deep Learning 52

Deep Learning Python Machine Learning Data Science 52

ProjectPro

JANUARY 10, 2022

Time series data can be defined as a sequence of data points that need to be seen with respect to the time stamp for each sample. Data samples are indexed by the timestamps or are highly dependent on them in time series. Time series forecasting involves predicting future values based on historical time-series data.

Python 52

Python Building Machine Learning Datasets 52

DareData

NOVEMBER 28, 2023

Nowadays, the next step for a Junior Data Scientist to get into real-life projects resides in understanding how to gather, manage and organize information on different high-performing machine learning models; deploy them into production; and monitor the performance.

Data Science 52

Data Science Medical Machine Learning Data 52

Picnic Engineering

MARCH 6, 2023

Note: This is Part II of the series. In Part I , we saw why building a simulation was the only way we could deliver a working final product on time. In any field of engineering, it is used to improve products as much as possible before they are used by the general public. But what does “real” mean for warehouse software?

Transportation 80

Transportation Java Software Engineer Software Engineering 80