Knowledge Hut

NOVEMBER 20, 2023

In this blog, I'll go into the interesting world of AI fraud detection, looking at how it works, its applications, benefits, and drawbacks. In essence, it's the use of AI anomaly detection algorithms, often covered in an Artificial Intelligence course for beginners , to analyze and identify suspicious activities or transactions.

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AltexSoft

AUGUST 25, 2021

But today’s programs, armed with machine learning and deep learning algorithms, go beyond picking the right line in reply, and help with many text and speech processing problems. For example, tokenization (splitting text data into words) and part-of-speech tagging (labeling nouns, verbs, etc.) Preparing an NLP dataset.

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ProjectPro

JANUARY 19, 2022

Source: Image uploaded by Tawfik Borgi on (researchgate.net) So, what is the first step towards leveraging data? The first step is to work on cleaning it and eliminating the unwanted information in the dataset so that data analysts and data scientists can use it for analysis.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

RandomTrees

DECEMBER 20, 2023

Most of today’s edge AI algorithms perform local inference directly on data that the device sees directly. Once trained, the model begins to answer real-world questions through an “inference engine.” Instead of manually updating the models, the updates get uploaded to the cloud, which reduces privacy concerns.

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IT Hospitality Healthcare Deep Learning 52

ProjectPro

OCTOBER 18, 2021

Machine Learning Projects are the key to understanding the real-world implementation of machine learning algorithms in the industry. Datasets like Google Local, Amazon product reviews, MovieLens, Goodreads, NES, Librarything are preferable for creating recommendation engines using machine learning models. Source: Moneyexcel 4.

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Databand.ai

JUNE 14, 2023

Ryan Yackel June 14, 2023 Understanding Data Quality Testing Data quality testing refers to the evaluation and validation of a dataset’s accuracy, consistency, completeness, and reliability. Risk mitigation: Data errors can result in expensive mistakes or even legal issues.

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AltexSoft

AUGUST 3, 2021

Now, the primary function of data labeling is tagging objects on raw data to help the ML model make accurate predictions and estimations. That said, data annotation is key in training ML models if you want to achieve high-quality outputs. This blog entry is particularly helpful to anyone who wants to.

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Cloudera

DECEMBER 17, 2020

When many businesses start their journey into ML and AI, it’s common to place a lot of energy and focus on the coding and data science algorithms themselves. First and foremost, we designed the Cloudera Data Platform (CDP) to optimize every step of what’s required to go from raw data to AI use cases.

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ProjectPro

JUNE 9, 2021

This blog on Data Science vs. Data Engineering presents a detailed comparison between the two domains. Data Science- Definition Data Science is an interdisciplinary branch encompassing data engineering and many other fields. It entails generating data visualizations and charts for analysis.

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Data Engineering Data Engineer Engineering Amazon Web Services 52

Cloudera

SEPTEMBER 13, 2018

Feature engineering, or the process of transforming raw data into a chosen representation of the underlying problem to be solved, is the data science process most ripe for automation. Before any machine learning can be applied to a business problem, data scientists need to define the problem itself.

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ProjectPro

JULY 12, 2021

Companies are actively seeking talent in these areas, and there is a huge market for individuals who can manipulate data, work with large databases and build machine learning algorithms. While data science is the most hyped-up career path in the data industry, it certainly isn't the only one. What does an AI Engineer do?

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ProjectPro

FEBRUARY 19, 2021

Therefore, it is necessary to detect them early on or use algorithms resistant to outliers. The equation for polynomial regression would obviously be a multinomial one: y = a + bX + cX 2 + dX 3 …… Before we go any further, let me introduce a concept called loss function, used to assess the usefulness of our regression algorithm.

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Knowledge Hut

DECEMBER 26, 2023

If we look at history, the data that was generated earlier was primarily structured and small in its outlook. A simple usage of Business Intelligence (BI) would be enough to analyze such datasets. However, as we progressed, data became complicated, more unstructured, or, in most cases, semi-structured. What is Data Science?

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Data Engineering Data Engineer Engineering Pipeline-centric 98

Edureka

JANUARY 18, 2024

It also discusses available resources and tools, and the current data science landscape. For those looking to start learning in 2024, here is a data science roadmap to follow. What is Data Science? They manage intricate datasets, create forecasting models, and examine consumer behavior to deliver tailored experiences.

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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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Databand.ai

JULY 6, 2023

7 Data Pipeline Examples: ETL, Data Science, eCommerce, and More Joseph Arnold July 6, 2023 What Are Data Pipelines? Data pipelines are a series of data processing steps that enable the flow and transformation of raw data into valuable insights for businesses.

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ProjectPro

OCTOBER 27, 2021

This blog presents the topmost useful machine learning applications in finance to help you understand how financial markets thrive by adopting AI and ML solutions. The huge volumes of financial data have helped the finance industry streamline processes, reduce investment risks, and optimize investment portfolios for clients and companies.

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Edureka

AUGUST 2, 2023

Raw data, however, is frequently disorganised, unstructured, and challenging to work with directly. Data processing analysts can be useful in this situation. Let’s take a deep dive into the subject and look at what we’re about to study in this blog: Table of Contents What Is Data Processing Analysis?

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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?

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Rockset

MAY 8, 2023

In this blog, we capture engineering stories from 5 early adopters of vector search- Pinterest, Spotify, eBay, Airbnb and Doordash- who have integrated AI into their applications. Embedded content: [link] Given a query, we can then find the most similar items in the dataset. What is vector search?

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ProjectPro

AUGUST 16, 2021

FAQs on Machine Learning Projects for Resume Machine Learning Projects for Resume - A Must-Have to Get Hired in 2021 Machine Learning and Data Science have been on the rise in the latter part of the last decade. Quite similar to classification is clustering but with the minor difference of working with unlabelled data.

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Edureka

SEPTEMBER 11, 2023

Business Intelligence (BI) is a set of technologies, software applications, and methods that help organizations collect, store, analyze, and make sense of large amounts of raw data to get insights that can be used to make decisions. The main goal of BI systems is to make it easier for businesses to make decisions based on data.

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AltexSoft

JANUARY 26, 2022

For more detailed information on data science team roles, check our video. An analytics engineer is a modern data team member that is responsible for modeling data to provide clean, accurate datasets so that different users within the company can work with them. Data modeling. What is an analytics engineer?

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ProjectPro

AUGUST 24, 2021

Nevertheless, that is not the only job in the data world. 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.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Databand.ai

JULY 28, 2022

What is Data Lineage? Niv Sluzki 2022-07-28 10:20:02 The term “data lineage” has been thrown around a lot over the last few years. What started as an idea of connecting between datasets quickly became a very confusing term that now gets misused often. This technique focuses directly on the data (vs.

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Metadata Data Lake Datasets Data Warehouse 52

ProjectPro

APRIL 12, 2021

The curse of dimensionality (the problems that arise when working with high-dimensional data) is a common problem when working on machine learning or deep learning projects. A general thumb rule between choosing PCA and Autoencoders is the size of data. Increasing the size of the training dataset. Use batch normalization.

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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?

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U-Next

AUGUST 3, 2022

After understanding what Data Science is and its fundamental principles, what else do we need to discuss? What is a Data Scientist? A Data Scientist is skilled in concluding data using various systems, procedures, and algorithms. That’s why our blog focuses on Data Scientist roles and responsibilities in India.

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Retail Data Science Computer Science Entertainment 52

Netflix Tech

NOVEMBER 12, 2019

Over the years, we have built a recommendation system that uses many different machine learning algorithms to create these personalized recommendations. All of these algorithms and logic come together in our page generation system to produce a personalized homepage for each of our members, which we have outlined in a previous post.

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Netflix Tech

NOVEMBER 12, 2019

Over the years, we have built a recommendation system that uses many different machine learning algorithms to create these personalized recommendations. All of these algorithms and logic come together in our page generation system to produce a personalized homepage for each of our members, which we have outlined in a previous post.

Algorithm 40

Algorithm Machine Learning Entertainment Systems 40

Netflix Tech

NOVEMBER 12, 2019

Over the years, we have built a recommendation system that uses many different machine learning algorithms to create these personalized recommendations. All of these algorithms and logic come together in our page generation system to produce a personalized homepage for each of our members, which we have outlined in a previous post.

Algorithm 40

Algorithm Machine Learning Entertainment Systems 40

ProjectPro

JULY 27, 2021

This blog is your one-stop solution for the top 100+ Data Engineer Interview Questions and Answers. In this blog, we have collated the frequently asked data engineer interview questions based on tools and technologies that are highly useful for a data engineer in the Big Data industry.

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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

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.

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Data Engineering Data Engineer Engineering Data Lake 52

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.

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Big Data Coding Project Hadoop 52

AltexSoft

DECEMBER 15, 2021

On the surface, ML algorithms take the data, develop their own understanding of it, and generate valuable business insights and predictions — all without human intervention. It boosts the performance of ML specialists relieving them of repetitive tasks and enables even non-experts to experiment with smart algorithms.

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ProjectPro

MARCH 14, 2014

Online FM Music 100 nodes, 8 TB storage Calculation of charts and data testing 16 IMVU Social Games Clusters up to 4 m1.large Job site 15 nodes Runs Machine learning Algorithms 44 CDU now! Online FM Music 100 nodes, 8 TB storage Calculation of charts and data testing 16 IMVU Social Games Clusters up to 4 m1.large

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