AltexSoft

AUGUST 25, 2021

There are two main steps for preparing data for the machine to understand. Any ML project starts with data preparation. You can’t simply feed the system your whole dataset of emails and expect it to understand what you want from it. What should it be like and how to prepare a great one?

Process 139

Process Deep Learning Datasets Machine Learning 139

Cloudera

FEBRUARY 8, 2023

I was looking for some broken code to add a workshop to our Spark Performance Tuning class and write a blog post about, and this fitted the bill perfectly. For convenience purposes I chose to limit the scope of this exercise to a specific function that prepares the data prior to the churn analysis. distinct().collect()

Java 56

Java Datasets Coding Python 56

Cloudera

DECEMBER 17, 2020

While it’s important to have the in-house data science expertise and the ML experts on-hand to build and test models, the reality is that the actual data science work — and the machine learning models themselves — are only one part of the broader enterprise machine learning puzzle. Laurence Goasduff, Gartner.

Machine Learning 79

Machine Learning Data Science Data Pipeline Raw Data 79

Rockset

SEPTEMBER 14, 2021

Rockset indexes the entire data stream so when new fields are added, they are immediately exposed and made queryable using SQL. We’ve also enabled the ingest of historical and real-time streams so that customers can access a 360 view of their data, a common real-time analytics use case.

Kafka 52

Kafka SQL MongoDB Computer Science 52

Scott Logic

MARCH 25, 2024

In this blog we will look at three of the leading tools, Microsoft Power BI, Amazon Quicksight and Tableau. There is a preferred workflow to guide a user through the steps of data preparation, analysis and visualisation but this workflow is not mandatory. An experienced user is free to work in whatever fashion suits them.

BI 52

BI Business Intelligence Cloud AWS 52

ProjectPro

JANUARY 15, 2021

Undoubtedly, everyone knows that the only best way to learn data science and machine learning is to learn them by doing diverse projects. Table of Contents What is a dataset in machine learning? Why you need machine learning datasets? Where can I find datasets for machine learning? Why you need machine learning datasets?

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Datasets Machine Learning Retail Banking 40

ProjectPro

FEBRUARY 21, 2023

With so many data engineering certifications available , choosing the right one can be a daunting task. There are over 133K data engineer job openings in the US, but how will you stand out in such a crowded job market? Why Are Data Engineering Skills In Demand? Don’t worry!

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Knowledge Hut

JANUARY 25, 2024

It doesn't matter if you're a data expert or just starting out; knowing how to clean your data is a must-have skill. The future is all about big data. This blog is here to help you understand not only the basics but also the cool new ways and tools to make your data squeaky clean. What is Data Cleaning?

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Data Cleanse Datasets Data Preparation Data Science 52

Rockset

FEBRUARY 7, 2020

Querying the IoT Data Available fields in the Rockset collection The above shows all the fields available in the collection which is used in the following queries. Note that we did not have to predefine a schema or perform any data preparation to get data in Kafka to be queryable in Rockset.

Kafka 40

Kafka Transportation Data SQL 40

AltexSoft

FEBRUARY 21, 2023

This blog post will delve into the challenges, approaches, and algorithms involved in hotel price prediction. For machine learning algorithms to predict prices accurately, people who do the data preparation must consider these factors and gather all this information to train the model. Data relevance. Public datasets.

Hospitality 52

Hospitality Datasets Algorithm Machine Learning 52

AltexSoft

MAY 12, 2021

Particularly, we’ll present our findings on what it takes to prepare a medical image dataset, which models show best results in medical image recognition , and how to enhance the accuracy of predictions. Otherwise, let’s proceed to the first and most fundamental step in building AI-fueled computer vision tools — data preparation.

Medical 72

Medical Healthcare Datasets Machine Learning 72

ProjectPro

JANUARY 31, 2023

However, collecting and annotating large amounts of data might not always be possible, and it is also expensive and time-consuming. Bid goodbye to worries related to such problems with this blog, as it covers an appropriate and effective solution to the problem of limited data available for training machine learning and deep learning models.

Deep Learning 52

Deep Learning Datasets Machine Learning Data 52

ProjectPro

MAY 20, 2015

There are several big data and business analytics companies that offer a novel kind of big data innovation through unprecedented personalization and efficiency at scale. Which big data analytic companies are believed to have the biggest potential? Why work at Palantir Technologies?

Big Data 40

Big Data Hadoop Business Analyst Unstructured Data 40

Knowledge Hut

JANUARY 24, 2024

If you are an expert in working with data or a beginner excited to use visualization, this blog will help you understand the differences between power bi and tableau. Tableau, on the other hand, stands out for its exceptional speed, ensuring swift rendering even when dealing with large and complex datasets.

BI 98

BI Business Intelligence Non-relational Database Data Analysis 98

Precisely

DECEMBER 4, 2023

They also need a strong foundation of data science to underpin those efforts. Many organizations get bogged down with data preparation, which can consume up to 80% of data science efforts. Collecting, organizing, and cleaning datasets consumes 45-60% of DS time.

Telecommunication 64

Telecommunication Data Science Data Integration Data Preparation 64

ProjectPro

AUGUST 24, 2021

Data professionals who work with raw data like data engineers, data analysts, machine learning scientists , and machine learning engineers also play a crucial role in any data science project. And, out of these professions, this blog will discuss the data engineering job role.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Snowflake

JUNE 28, 2023

Snowpark is our secure deployment and processing of non-SQL code, consisting of two layers: Familiar Client Side Libraries – Snowpark brings deeply integrated, DataFrame-style programming and OSS compatible APIs to the languages data practitioners like to use.

Python 52

Python Accessible Accessibility Pipeline-centric 52

Knowledge Hut

DECEMBER 7, 2023

In this blog, I'll define the AI project life cycle and walk you through the steps, tools, and significance of the AI model lifecycle management process. This includes configuring hyperparameters, training the model on the training data, and fine-tuning it. They provide functions for cleaning, transforming, and analyzing data.

Machine Learning 52

Machine Learning Algorithm Medical Government 52

ProjectPro

JANUARY 19, 2022

Planning to land a successful job as an Azure Data Engineer? Read this blog till the end to learn more about the roles and responsibilities, necessary skillsets, average salaries, and various important certifications that will help you build a successful career as an Azure Data Engineer. The final step is to publish your work.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

ProjectPro

FEBRUARY 8, 2023

Do ETL and data integration activities seem complex to you? Read this blog to understand everything about AWS Glue that makes it one of the most popular data integration solutions in the industry. Did you know the global big data market will likely reach $268.4 Businesses are leveraging big data now more than ever.

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AWS Scala Metadata Data Lake 98

ProjectPro

JANUARY 31, 2023

If you're looking to break into the exciting field of big data or advance your big data career, being well-prepared for big data interview questions is essential. Get ready to expand your knowledge and take your big data career to the next level! But the concern is - how do you become a big data professional?

Big Data 52

Big Data Hadoop AWS Relational Database 52

Rockset

FEBRUARY 24, 2022

While this blog post won’t dive deeply into Kinesis’ capabilities, it’s worth quickly noting three: Kinesis Data Streams enable continuous capture of gigabytes of data per second from an enormous number of sources. Rockset You didn’t think you’d finish a Rockset blog post without hearing about Rockset, did you?

AWS 52

AWS Amazon Web Services Kafka SQL 52

Picnic Engineering

MAY 23, 2023

At Picnic, we understand the importance of efficient and accurate customer service, which is why we’ve turned to natural language processing techniques to automate the classification of customer feedback as you can read in this and this blog post. This is why we conclude that further improvements are likely possible.

Machine Learning 72

Machine Learning Algorithm Deep Learning Architecture 72

AltexSoft

SEPTEMBER 13, 2023

In the world of machine learning , there’s a well-known saying, “An ML model is only as good as the training data you feed it with.” It points out the critical role that data quality plays in the outcomes you get from these algorithms. Watch our video about data preparation for ML tasks to learn more about this.

Engineering 59

Engineering Hospitality Transportation Algorithm 59

U-Next

JUNE 29, 2022

However, the benefits might be game-changing: a well-designed big data pipeline can significantly differentiate a company. In this blog, we’ll go over elements of big data , the big data environment as a whole, big data infrastructures, and some valuable tools for getting it all done.

Big Data 40

Big Data Big Data Ecosystem Data Lake Raw Data 40

Rockset

FEBRUARY 25, 2021

Instead, this data is often semi-structured in JSON or arrays. Often this lack of structure forces developers to spend a lot of their time engineering ETL and data pipelines so that analysts can access the complex datasets. This takes a lot of time and is often a slow process that doesn’t work well for anybody.

SQL 40

SQL Data Pipeline Kafka Database 40

ProjectPro

NOVEMBER 15, 2021

Table of Contents 20 Open Source Big Data Projects To Contribute How to Contribute to Open Source Big Data Projects? 20 Open Source Big Data Projects To Contribute There are thousands of open-source projects in action today. This blog will walk through the most popular and fascinating open source big data projects.

Big Data 52

Big Data Project Metadata Programming Language 52

AltexSoft

MAY 14, 2021

As you now know the key characteristics, it gets clear that not all data can be referred to as Big Data. What is Big Data analytics? Big Data analytics is the process of finding patterns, trends, and relationships in massive datasets that can’t be discovered with traditional data management techniques and tools.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Cloudera

OCTOBER 17, 2017

In this blog, we provide a few examples that show how organizations put deep learning to work. Next, we introduce you to Cloudera’s unified platform for data and machine learning and show you four ways to implement deep learning. Move forward with Cloudera, the unified platform for data and machine learning.

Deep Learning 46

Deep Learning Scala Medical Data Science 46

ProjectPro

JANUARY 31, 2022

Launched in 2014, Snowflake is one of the most popular cloud data solutions on the market. This blog walks you through what does Snowflake do , the various features it offers, the Snowflake architecture, and so much more. Table of Contents Snowflake Overview and Architecture What is Snowflake Data Warehouse?

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Architecture IT Data Warehouse Amazon Web Services 52

ProjectPro

OCTOBER 20, 2021

If you are unsure, be vocal about your thought process and the way you are thinking – take inspiration from the examples below and explain the answer to the interviewer through your learnings and experiences from data science and machine learning projects. It will explain what an instance of the best-in-class answers would sound like.

Machine Learning 52

Machine Learning Algorithm Government Data Science 52

LinkedIn Engineering

DECEMBER 20, 2023

This blog post delves into the AutoML framework for LinkedIn’s content abuse detection platform and its role in improving and fortifying content moderation systems at LinkedIn. It enables models to stay updated by automatically retraining on incrementally larger and more recent data with a pre-defined periodicity.

Machine Learning 90

Machine Learning Datasets Algorithm Architecture 90

ProjectPro

MAY 31, 2021

Ace your big data interview by adding some unique and exciting Big Data projects to your portfolio. This blog lists over 20 big data projects you can work on to showcase your big data skills and gain hands-on experience in big data tools and technologies.

Big Data 52

Big Data Coding Project Hadoop 52

Cloudera

OCTOBER 11, 2021

The platform converges data cataloging, data ingestion, data profiling, data tagging, data discovery, and data exploration into a unified platform, driven by metadata. Modak Nabu automates repetitive tasks in the data preparation process and thus accelerates the data preparation by 4x.

Data Engineering 89

Data Engineering Data Engineer Cloud Engineering 89

RandomTrees

FEBRUARY 6, 2024

Over the years, the field of data engineering has seen significant changes and paradigm shifts driven by the phenomenal growth of data and by major technological advances such as cloud computing, data lakes, distributed computing, containerization, serverless computing, machine learning, graph database, etc.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

AltexSoft

DECEMBER 15, 2021

Namely, AutoML takes care of routine operations within data preparation, feature extraction, model optimization during the training process, and model selection. In the meantime, we’ll focus on AutoML which drives a considerable part of the MLOps cycle, from data preparation to model validation and getting it ready for deployment.

Machine Learning 59

Machine Learning Deep Learning Algorithm Telecommunication 59

LinkedIn Engineering

DECEMBER 13, 2022

In this blog post, we share more details on how LinkedIn performs observational causal inference at scale using our Ocelot platform. We chose to bundle the functionality of data preparation with the causal modeling for the following reasons.�� We fine tuned Spark jobs to reduce the data preparation time and failure rate.

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Data Preparation Data Science Designing Data Pipeline 55