Knowledge Hut

DECEMBER 22, 2023

Data analytics, data mining, artificial intelligence, machine learning, deep learning, and other related matters are all included under the collective term "data science" When it comes to data science, it is one of the industries with the fastest growth in terms of income potential and career opportunities.

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ProjectPro

FEBRUARY 16, 2023

The study and pattern of how humans think is the foundation of artificial intelligence, and the algorithm replicates human brain functions. Artificial Intelligence: Tools and Technologies Artificial Intelligence uses complex algorithms to make logic. It uses the BFS (Breadth First Search) algorithm and operates on the FIFO principle.

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Pinterest Engineering

JANUARY 18, 2024

Our engineers are constantly discovering new algorithms and new signals to improve the performance of our machine learning models. We’ve since transitioned to a Unified Feature Representation (flattened feature definitions), making ML features a priority in the ML lifecycle.

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DareData

SEPTEMBER 14, 2024

Managing the expectation of speed and accuracy of algorithms is absolutely crucial. Don’t promise high accuracy / f-score / other metric without seeing the data. The success metric definition is your friend. Don’t promise high speed without assessing the company’s systems and ability to scale.

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ProjectPro

FEBRUARY 8, 2016

It is the simplest form of analytics, and it describes or summarises the existing data using existing business intelligence tools. The main techniques used here are data mining and data aggregation. Descriptive analytics involves using descriptive statistics such as arithmetic operations on existing data.

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Knowledge Hut

APRIL 26, 2024

Let's take a look at all the fuss about data science , its courses, and the path to the future. What is Data Science? In order to discover insights and then analyze multiple structured and unstructured data, Data Science requires the use of different instruments, algorithms and principles.

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Edureka

SEPTEMBER 23, 2024

Data Science vs Artificial Intelligence: Key Differences Aspect Data Science Artificial Intellignce Definition An academic discipline that involves the study of facts and figures and aims at their interpretation. Encompasses developing algorithms and models that enable machines to perform tasks requiring human intelligence.

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ProjectPro

JUNE 18, 2021

Java is also used by many big companies including Uber and Airbnb to process their backend algorithms. Java for Data Science - Should data scientists learn Java? Is Java right for your data science projects? SciKit-learn: The SciKit-learn library of Python can be used for data mining and data analysis.

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ProjectPro

JUNE 9, 2021

As we proceed further into the blog, you will find some statistics on data engineering vs. data science jobs and data engineering vs. data science salary, along with an in-depth comparison between the two roles- data engineer vs. data scientist. vs. What does a Data Engineer do?

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Knowledge Hut

JUNE 16, 2023

Machine learning is the domain under artificial intelligence, devoted to using algorithms that help machines learn things like humans. The algorithms use historical data as input to predict the outputs until the machine gains human-like proficiency.

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ProjectPro

NOVEMBER 3, 2021

The same holds for employees working as Data Scientists as well. Working as a freelance data scientist may not seem rewarding initially, but it is definitely a gratifying career option in the long run. As a freelance data scientist, you get to control your working hours and lifestyle.

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ProjectPro

MAY 23, 2015

With more than 245 million customers visiting 10,900 stores and with 10 active websites across the globe, Walmart is definitely a name to reckon with in the retail sector. Inkiru's predictive technology platform pulls data from diverse sources and helps Walmart improve personalization through data analytics.

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ProjectPro

OCTOBER 28, 2021

If you think machine learning methods may not be of use to you, we reckon you reconsider that because, in May 2021, Gartner has revealed that about 70% of organisations will shift their focus from big to small and wide data by 2025. Those functions have been optimised already, so you don’t need to go in depth of the algorithms.

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Knowledge Hut

DECEMBER 26, 2023

In this list, you will find the best data scientist books to take you further in your career as a data scientist. Deep Learning By Ian Goodfellow, Yoshua Bengio, and Aaron Courville As an advanced learner, this book should be your Bible for learning about deep learning algorithms.

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Knowledge Hut

JUNE 10, 2024

Pattern Among the various Python frameworks available, Pattern is particularly well-suited for Data Science tasks. It provides a comprehensive set of tools for Data Mining, Machine learning, and Natural Language Processing. Scikit-Learn Scikit-Learn is one of the best Python Data Science frameworks for Machine learning.

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Knowledge Hut

FEBRUARY 12, 2023

It involves complex calculations applied to data collected and refined to conclude. Python Programming Python is a computer language with built-in mathematical libraries and functions to write algorithms for data processing tools. Python allows a data science professional to create user-friendly tools to process extensive data.

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ProjectPro

OCTOBER 18, 2021

Machine Learning Projects are the key to understanding the real-world implementation of machine learning algorithms in the industry. Regression analysis: This technique talks about the predictive methods that your system will execute while interacting between dependent variables (target data) and independent variables (predictor data).

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Zalando Engineering

FEBRUARY 1, 2017

Filters offer a static set of dimensions to narrow down content; usually built offline using data mining techniques. Sorting algorithms consider static aspects of the content such as brand, category, and dynamic aspects - availability, merchant rank, delivery time etc.

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U-Next

OCTOBER 27, 2022

AI is a branch of computer science that deals with making computers intelligent by writing algorithms with human-like characteristics like learning and problem-solving. These algorithms learn from large data sets, which are processed through CPUs or GPUs depending on their type of application. . The most popular methods are:

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U-Next

OCTOBER 16, 2022

AI is a branch of computer science that deals with making computers intelligent by writing algorithms with human-like characteristics like learning and problem-solving. These algorithms learn from large data sets, which are processed through CPUs or GPUs depending on their type of application. . The most popular methods are:

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Knowledge Hut

JANUARY 18, 2024

In this article, I'll walk you through the fundamentals of Naive Bayes, a robust machine learning algorithm. Understanding conditional probability is crucial in various fields, aiding in decision-making, statistical analysis, and machine learning, where it plays a pivotal role in algorithms like Naive Bayes.

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U-Next

SEPTEMBER 19, 2022

If you are prepared to put in the required time and effort and are open to learning new things, you’ll surely become a successful Data Scientist. The opportunities for Data Scientists are unending. Enterprises in all fields definitely would want to employ people with more skills. Data Mining.

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ProjectPro

JULY 3, 2015

The combined potential of Apache Hadoop’s parallel processing of large datasets and HANA’s in-memory computing capabilities offers- Cost effective solutions for large scale data storage and processing of both structured , semi structured and unstructured data such as text, video,audio,web logs, and machine data.

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Knowledge Hut

FEBRUARY 15, 2023

The openings for entry-level data analyst jobs are surging rapidly across domains like finance, business intelligence, Economy services, and so on, and the US is no exception. Data analyst experts can also enjoy the luxury of working remotely for top recruiters in the US at considerably high pay scales. What is Data Analysis?

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Knowledge Hut

DECEMBER 27, 2023

Accessing and storing huge data volumes for analytics was going on for a long time. But ‘big data’ as a concept gained popularity in the early 2000s when Doug Laney, an industry analyst, articulated the definition of big data as the 3Vs. No doubt companies are investing in big data and as a career, it has huge potential.

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Knowledge Hut

SEPTEMBER 25, 2023

Is Data Analyst Certification worth it? In my opinion, Data analyst certification is definitely worth it. You can utilize previous data to forecast outcomes with the aid of tools like machine learning, algorithms, and protective modeling, which is especially pertinent in the financial and sales industries.

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Knowledge Hut

SEPTEMBER 6, 2023

Statistical Knowledge : It is vital to be familiar with statistical procedures and techniques in order to assess data and form trustworthy conclusions. Data Mining and ETL : For gathering, transforming, and integrating data from diverse sources, proficiency in data mining techniques and Extract, Transform, Load (ETL) processes is required.

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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. Machine learning algorithms learn from data.

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ProjectPro

AUGUST 11, 2021

Analysis Layer: The analysis layer supports access to the integrated data to meet its business requirements. The data may be accessed to issue reports or to find any hidden patterns in the data. Data mining may be applied to data to dynamically analyze the information or simulate and analyze hypothetical business scenarios.

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U-Next

SEPTEMBER 21, 2022

Read this article to learn how a massive amount of data is collected, organized, and processed to extract useful information using data warehousing and data mining. You will also understand the Difference between Data Warehousing and Data Mining in a detailed manner. . What Is Data Warehousing? .

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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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U-Next

AUGUST 3, 2022

Although the term “Data Science” might imply various things to various individuals, it is essentially the use of data to provide answers to inquiries. This definition is rather wide because Data Science is, undoubtedly, a somewhat vast discipline! What is a Data Scientist?

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ProjectPro

MAY 31, 2021

A big data project is a data analysis project that uses machine learning algorithms and different data analytics techniques on a large dataset for several purposes, including predictive modeling and other advanced analytics applications. Advanced data scientists can use supervised algorithms to predict future trends.

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AltexSoft

MAY 12, 2023

By understanding these aspects comprehensively, you can harness the true potential of unstructured data and transform it into a strategic asset. What is unstructured data? Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization.

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Knowledge Hut

DECEMBER 26, 2023

Data science is a subject of study that utilizes scientific methods, processes, algorithms, and systems to uproot knowledge and insights from data in various forms, both structured and unstructured. Data science is related to data mining and big data.

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