Knowledge Hut

MAY 3, 2024

If you are thinking of a simple, easy-to-implement supervised machine learning algorithm that can be used to solve both classifications as well as regression problems, K-Nearest Neighbors (K-NN) is a perfect choice. K-Nearest Neighbors is one of the most basic supervised machine learning algorithms, yet very essential.

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Machine Learning Algorithm Datasets Python 52

Knowledge Hut

MARCH 22, 2024

Understanding data structures and algorithms (DSA) in C++ is key for writing efficient and optimised code. Some basic DSA in C++ that every programmer should know include arrays, linked lists, stacks, queues, trees, graphs, sorting algorithms like quicksort and merge sort, and search algorithms like binary search.

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Algorithm Programming Data Datasets 52

ProjectPro

JUNE 22, 2021

This blog will help you master the fundamentals of classification machine learning algorithms with their pros and cons. You will also explore some exciting machine learning project ideas that implement different types of classification algorithms. So, without much ado, let's dive in.

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Netflix Tech

NOVEMBER 20, 2023

by Jun He , Yingyi Zhang , and Pawan Dixit Incremental processing is an approach to process new or changed data in workflows. The key advantage is that it only incrementally processes data that are newly added or updated to a dataset, instead of re-processing the complete dataset.

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ProjectPro

NOVEMBER 25, 2021

To mitigate this challenge, organizations are now leveraging natural language processing and machine learning techniques to extract meaningful insights from unstructured text data. Read this blog to learn about text classification, one of the core topics of natural language processing. Table of Contents What is Text Classification?

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AltexSoft

AUGUST 25, 2021

And this technology of Natural Language Processing is available to all businesses. Available methods for text processing and which one to choose. What is Natural Language Processing? Natural language processing or NLP is a branch of Artificial Intelligence that gives machines the ability to understand natural human speech.

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AltexSoft

OCTOBER 18, 2022

In this post, we’ll briefly discuss challenges you face when working with medical data and make an overview of publucly available healthcare datasets, along with practical tasks they help solve. At the same time, de-identification only encrypts personal details and hides them in separate datasets. Medical datasets comparison chart .

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Knowledge Hut

JULY 28, 2023

Data Labeling is the process of assigning meaningful tags or annotations to raw data, typically in the form of text, images, audio, or video. These labels provide context and meaning to the data, enabling machine learning algorithms to learn and make predictions. The more data we feed, the better the model gets.

Machine Learning 52

Machine Learning Process Datasets Raw Data 52

Knowledge Hut

JANUARY 18, 2024

“Big data Analytics” is a phrase that was coined to refer to amounts of datasets that are so large traditional data processing software simply can’t manage them. Big data frameworks are instruments that simplify the processing of big data. It then transfers code into the nodes for processing data in parallel.

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ProjectPro

NOVEMBER 8, 2021

Whether it is quality control of crops through image classification or image processing for electronic deposits, computer vision techniques are transforming industries across the globe. The performance of computer vision algorithms has surpassed humans in specific tasks like detecting and labeling objects in terms of speed and accuracy.

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Algorithm Medical Datasets Python 52

The Pragmatic Engineer

OCTOBER 17, 2024

The historical dataset is over 20M records at the time of writing! Code and raw data repository:   Version control: GitHub Heavily using GitHub Actions for things like getting warehouse data from vendor APIs, starting cloud servers, running benchmarks, processing results, and cleaning up after tuns.

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Knowledge Hut

FEBRUARY 1, 2024

You can try some hands-on with online datasets to gain practical exposure. Data cleaning is the process of identifying and fixing incorrect data. In this article, we will look at eight common steps in the data cleaning process, as mentioned below. What is Data Cleaning in Data Science?

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Edureka

JULY 5, 2024

Proper data pre-processing and data cleaning in data analysis constitute the starting point and foundation for effective decision-making, though it can be the most tiresome phase. Smart recommendations: Utilizes machine learning algorithms to suggest and automate data cleaning and transformation tasks, saving time and improving efficiency.

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Data Preparation Process BI ETL Tools 40

Databand.ai

JULY 6, 2023

Data Integrity Testing: Goals, Process, and Best Practices Niv Sluzki July 6, 2023 What Is Data Integrity Testing? Data integrity testing refers to the process of validating the accuracy, consistency, and reliability of data stored in databases, data warehouses, or other data storage systems.

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Data Integration Process Data Validation Data Governance 52

Knowledge Hut

MAY 2, 2024

Machine learning is a field that encompasses probability, statistics, computer science and algorithms that are used to create intelligent applications. Since machine learning is all about the study and use of algorithms, it is important that you have a base in mathematics. It works on a large dataset.

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Machine Learning Algorithm Datasets Python 98

Knowledge Hut

FEBRUARY 1, 2024

Movie recommender systems are intelligent algorithms that suggest movies for users to watch based on their previous viewing behavior & preferences. The heart of this system lies in the algorithm used in movie recommendation system. The heart of this system lies in the algorithm used in movie recommendation system.

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Systems Entertainment Algorithm Datasets 98

Edureka

AUGUST 2, 2023

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? What Does a Data Processing Analyst Do? What does a Data Processing Analysts do ?

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Engineering at Meta

NOVEMBER 12, 2024

Monitoring has given us a distinct advantage in our efforts to proactively detect and remove weak cryptographic algorithms and has assisted with our general change safety and reliability efforts. More generally, improved understanding helps us to make emergency algorithm migrations when a vulnerability of a primitive is discovered.

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Algorithm Datasets Coding Java 70

Knowledge Hut

JULY 28, 2023

By learning from historical data, machine learning algorithms autonomously detect deviations, enabling timely risk mitigation. Machine learning offers scalability and efficiency, processing large datasets quickly. By taking into account the statistical characteristics of the entire dataset, global outliers are frequently found.

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Knowledge Hut

JULY 24, 2023

As data generation continues to skyrocket, the demand for real-time decision-making, data processing, and analysis increases. Recently, the advent of stream processing has unlocked the door for a new era in database technology. One of its most significant benefits is its ability to quickly process a vast amount of data.

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Picnic Engineering

OCTOBER 14, 2024

This so-called Master Planning Process (MPP) represents the planning of the Picnic supply chain path for every ordered article from the Fulfilment Centre to the customer’s door. Combinatorial optimisation is the process of trying to find the optimal solution given a set of finite possibilities. What is combinatorial optimisation?

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Algorithm Datasets Java Coding 75

ProjectPro

JANUARY 15, 2021

And honestly, there are a lot of real-world machine learning datasets around you that you can opt to start practicing your fundamental data science and machine learning skills, even without having to complete a comprehensive data science or machine learning course. Table of Contents What is a dataset in machine learning?

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Machine Learning Datasets Retail Banking 40

ProjectPro

FEBRUARY 16, 2023

At the core of such applications lies the science of machine learning, image processing, computer vision, and deep learning. As an example, consider the Facial Image Recognition System, it leverages the OpenCV Python library for implementing image processing techniques. What is OpenCV Python?

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Knowledge Hut

MAY 2, 2024

To store and process even only a fraction of this amount of data, we need Big Data frameworks as traditional Databases would not be able to store so much data nor traditional processing systems would be able to process this data quickly. Spark is 10-100 times faster because of in-memory processing and its caching mechanism.

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Hadoop Scala Datasets Java 96

Knowledge Hut

MARCH 22, 2024

Reverse engineering software is the process of dissecting it to understand its components, functionality, and workflow without having access to the source code. 5 Steps of Reverse Engineering [Process] The process of reverse engineering can be broken down into five key steps. What is Reverse Engineering in Software Engineering?

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Process Engineering Electronics Software Engineering 52

AltexSoft

JULY 18, 2023

These seemingly unrelated terms unite within the sphere of big data, representing a processing engine that is both enduring and powerfully effective — Apache Spark. These components interact seamlessly with each other, making Spark a versatile and comprehensive platform for processing huge volumes of diverse information.

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Tweag

APRIL 19, 2023

Detecting cancerous cells in microscopic photography of cells (Whole Slide Images, aka WSIs) is usually done with segmentation algorithms, which NNs are very good at. To allow innovation in medical imaging with AI, we need efficient and affordable ways to store and process these WSIs at scale. _slides_specs. items ( ) : with fsspec.

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Knowledge Hut

APRIL 25, 2024

Recognizing the difference between big data and machine learning is crucial since big data involves managing and processing extensive datasets, while machine learning revolves around creating algorithms and models to extract valuable information and make data-driven predictions.

Machine Learning 52

Machine Learning Big Data Unstructured Data Data Mining 52

Edureka

JUNE 7, 2024

Generative AI leverages the power of deep learning to build complex statistical models that process and mimic the structures present in different types of data. These models are trained on vast datasets which allow them to identify intricate patterns and relationships that human eyes might overlook.

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ProjectPro

JANUARY 25, 2022

Furthermore, PySpark allows you to interact with Resilient Distributed Datasets (RDDs) in Apache Spark and Python. PySpark is a handy tool for data scientists since it makes the process of converting prototype models into production-ready model workflows much more effortless. You can accomplish this using the Py4j library.

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ProjectPro

JULY 9, 2021

With the help of natural language processing (NLP) tools, it has led to the development of exciting artificial intelligence applications like language recognition, autonomous vehicles, and computer vision robots, to name a few. Table of Contents Why Deep Learning Algorithms over Traditional Machine Learning Algorithms?

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Deep Learning Algorithm Machine Learning Datasets 40

ProjectPro

FEBRUARY 5, 2021

Image classification , a subfield of computer vision helps in processing and classifying objects based on trained algorithms. 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. instead of handwritten digits.

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Knowledge Hut

MAY 30, 2024

Natural Language Processing Techniques 2. Evolutionary Algorithms and their Applications 9. Machine Learning Algorithms 5. Digital Image Processing: 6. Edge computing, on the other hand, entails processing data close to the generation source, such as sensors and IoT devices. Artificial Intelligence (AI) 11.

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AltexSoft

DECEMBER 21, 2021

.” In this article, you will find out what data labeling is, how it works, which data labeling types exist, and what best practices to follow to make this process smooth as glass. In this case, the training dataset will consist of multiple songs with labels showing genres like pop, jazz, rock, etc. What is data labeling?

Machine Learning 52

Machine Learning Process Raw Data Datasets 52

Knowledge Hut

JULY 4, 2023

Pattern recognition is used in a wide variety of applications, including Image processing, Speech recognition, Biometrics, Medical diagnosis, and Fraud detection. And is used in a wide variety of applications, including image processing, speech recognition, and medical diagnosis.

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Machine Learning Medical Algorithm Deep Learning 98

Knowledge Hut

APRIL 23, 2024

Entails employing algorithms like classification, clustering, and the like for extracting relationships and patterns from data. Data Types Big Data Data Mining Big data refers to robust and complicated datasets that require a high level of expertise and tools for managing, processing, or analyzing.

Data Mining 52

Data Mining Big Data Database-centric Unstructured Data 52

Towards Data Science

OCTOBER 29, 2024

Balancing complexity and performance: An in-depth look at K-fold target encoding Photo by Mika Baumeister on Unsplash Introduction Data science practitioners encounter numerous challenges when handling diverse data types across various projects, each demanding unique processing methods.

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