Knowledge Hut

NOVEMBER 27, 2023

Transitioning to a career in data science has become increasingly attractive in recent years. The demand for qualified data professionals continues to rise as companies recognize the value of data-driven decision-making. What Do Data Scientists Do? Why Should You Get Into Data Science?

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Edureka

JANUARY 18, 2024

This guide provides a comprehensive understanding of the essential skills and knowledge required to become a successful data scientist, covering data manipulation, programming, mathematics, big data, deep learning, and machine learning technologies. What is Data Science?

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Knowledge Hut

JANUARY 22, 2024

FinTech companies depend heavily on FinTech data science to simplify financial decision-making and deliver cutting-edge solutions. So first, let's see what data science in fintech is and its importance. What is Data Science? Want to learn more about Data Science in FinTech?

Data Science 52

Data Science Banking Big Data Insurance 52

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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Knowledge Hut

DECEMBER 26, 2023

Companies from startups to the Fortune 500s are looking out for the best and brightest individuals to fill up the role of Data engineers beating out data scientists, cybersecurity analysts, and web developers. What is Data Science? What are the roles and responsibilities of a Data Engineer? What is Data Science?

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Cloudera

MAY 19, 2021

In the previous blog post in this series, we walked through the steps for leveraging Deep Learning in your Cloudera Machine Learning (CML) projects. RAPIDS on the Cloudera Data Platform comes pre-configured with all the necessary libraries and dependencies to bring the power of RAPIDS to your projects. Get the Dataset.

Machine Learning 137

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ProjectPro

APRIL 12, 2021

Deep learning job interviews. Most beginners in the industry break out in a cold sweat at the mere thought of a machine learning or a deep learning job interview. How do I prepare for my upcoming deep learning job interview? What kind of deep learning interview questions they are going to ask me?

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Knowledge Hut

JULY 4, 2023

Data analysis and Interpretation: It helps in analyzing large and complex datasets by extracting meaningful patterns and structures. By identifying and understanding patterns within the data, valuable insights can be gained, leading to better decision-making, and understanding of underlying relationships.

Machine Learning 98

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Knowledge Hut

MAY 30, 2024

While a single research paper is not enough to bring the light on an entire domain as vast as machine learning; it can help you witness how applicable it is in numerous fields, like engineering, data science & analysis, business intelligence, and many more. Welcome to the world of data-driven insights!

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AltexSoft

MAY 12, 2022

Aiming at understanding sound data, it applies a range of technologies, including state-of-the-art deep learning algorithms. For further steps, you need to load your dataset to Python or switch to a platform specifically focusing on analysis and/or machine learning. Labeling of audio data in Audacity.

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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. You can’t simply feed the system your whole dataset of emails and expect it to understand what you want from it. Preparing an NLP dataset.

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Edureka

AUGUST 2, 2023

In this digital transformation era, data is at the heart of decision-making. Data science has gained prominence, playing a crucial role in deriving insights from vast volumes of data. Aspiring data scientists must familiarize themselves with the best programming languages in their field.

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Knowledge Hut

JUNE 20, 2023

Many people are learning data science for the first time and need help comprehending the two job positions. Data science is relatively new, and roles and job titles occasionally change. Factors Data Engineer Machine Learning Definition Data engineers create, maintain, and optimize data infrastructure for data.

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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. What is Data Labeling for Machine Learning?

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AltexSoft

DECEMBER 15, 2021

AutoML objectives and benefits overlap with those of MLOps — a broader discipline with focus not only on automation but also on cross-functional collaboration within machine learning projects. feature engineering or feature extraction when useful properties are drawn from raw data and transformed into a desired form, and.

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RandomTrees

DECEMBER 20, 2023

To replicate human cognition, AI uses a system named deep neural network. Federated deep learning is also a promising technology that could improve edge AI’s privacy and security. As they get trained, these DNNs result in many examples of specific types of questions and the correct answers.

IT 52

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ProjectPro

FEBRUARY 25, 2022

Data Ingestion Data Processing Data Splitting Model Training Model Evaluation Model Deployment Monitoring Model Performance Machine Learning Pipeline Tools Machine Learning Pipeline Deployment on Different Platforms FAQs What tools exist for managing data science and machine learning pipelines?

Machine Learning 52

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ProjectPro

JUNE 9, 2021

This blog on Data Science vs. Data Engineering presents a detailed comparison between the two domains. vs. What does a Data Engineer do? Data Engineer: Skills Data Engineer vs Data Scientist: Salary How to Become a Data Scientist/Data Engineer?

Data Engineering 52

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Knowledge Hut

JUNE 20, 2023

Theano It is an open-source Python library for deep learning in neural processing and data science. With this tool, the creation and distribution of the networks get sorted, and you can conveniently handle larger datasets. Furthermore, it enables you to optimize the data without manual coding.

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ProjectPro

OCTOBER 18, 2021

Every final year student interested in pursuing a career in data science or machine learning must work on a hands-on project to experience a practical approach to how machine learning models are implemented and deployed in production. To build such ML projects, you must know different approaches to cleaning raw data.

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AltexSoft

JUNE 26, 2023

We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection? It’s the first and essential stage of data-related activities and projects, including business intelligence , machine learning , and big data analytics. No wonder only 0.5

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AltexSoft

DECEMBER 21, 2021

When people hear about artificial intelligence, deep learning, and machine learning , many think of movie-like robots that resemble or even outperform human intelligence. Others believe that such machines simply consume information and learn from it by themselves. So, what challenges does data labeling involve?

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U-Next

AUGUST 3, 2022

And Data Science has a significant impact here. Today, Data Science is expanding in many ways, so it’s important to understand what it is and how we can improve it to prepare for the future. Data Scientist roles and responsibilities have become increasingly challenging, fun, and worthwhile. .

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ProjectPro

AUGUST 16, 2021

Sending out the exact old traditional style data science or machine learning resume might not be doing any favours in your machine learning job search. With cut-throat competition in the industry for high-paying machine learning jobs, a boring cookie-cutter resume might not just be enough.

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ProjectPro

OCTOBER 29, 2021

Since then, many other well-loved terms, such as “data economy,” have come to be widely used by industry experts to describe the influence and importance of big data in today’s society. This is why we will get back to the über important topic of improving data quality by preprocessing in the later section.

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ProjectPro

JULY 26, 2021

TensorFlow is equipped with features, like state-of-the-art pre-trained models, p opular machine learning datasets , and increased ease of execution for mathematical computations, making it popular among seasoned researchers and students alike. Deep Learning in Medical Imaging using TensorFlow 5.

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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.

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ProjectPro

OCTOBER 27, 2021

Use the Pandas data frame to read and store your data. Also, remove all missing and NaN values from the dataset, as incomplete data is unnecessary. You can use the Huge Stock Market Dataset or the NY Stock Exchange Dataset to implement this machine learning project. Our data is imbalanced.

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Picnic Engineering

JULY 24, 2023

It’s also exciting to see that research in machine learning is looking at how more advanced methods, such as deep learning and transformers, can be used for even better demand forecasting. By converting raw data into valuable information, transformer models could significantly contribute to sustainability.

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AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

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AltexSoft

MAY 12, 2023

Data lakes offer a flexible and cost-effective approach for managing and storing unstructured data, ensuring high durability and availability. The Hadoop ecosystem also has various tools and libraries to manage large datasets. However, it may require more effort to learn than other solutions.

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ProjectPro

NOVEMBER 30, 2021

If you are into Data Science or Big Data, you must be familiar with an ETL pipeline. This guide provides definitions, a step-by-step tutorial, and a few best practices to help you understand ETL pipelines and how they differ from data pipelines. How do we transform this data to get valuable insights from it?

Process 52

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ProjectPro

AUGUST 24, 2021

Within no time, most of them are either data scientists already or have set a clear goal to become one. Nevertheless, that is not the only job in the data world. And, out of these professions, this blog will discuss the data engineering job role. The Yelp dataset JSON stream is published to the PubSub topic.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

JANUARY 31, 2022

Table of Contents Snowflake Overview and Architecture What is Snowflake Data Warehouse? Snowflake Features that Make Data Science Easier Building Data Applications with Snowflake Data Warehouse Snowflake Data Warehouse Architecture How Does Snowflake Store Data Internally? What Does Snowflake Do?

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

U-Next

AUGUST 25, 2022

The popular Machine Learning models and algorithms widely employed in the Artificial Intelligence business include supervised and unsupervised learning algorithms , random forest, k-nearest neighbor, and basics of deep learning. Machine Learning Types. Quantum Computing.

Machine Learning 40

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ProjectPro

DECEMBER 22, 2016

If you are planning to appear for a data analyst job interview, these interview questions for data analysts will help you land a top gig as a data analyst at one of the top tech companies. We have collected a library of solved Data Science use-case code examples that you can find here. 5) What is data cleansing?

Data Mining 52

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ProjectPro

FEBRUARY 19, 2021

Regression analysis is the favorite of data science and machine learning practitioners as it provides a great level of flexibility and reliability making it an ideal choice for analyzing different situations like - Do educational degrees and IQ affect salary? It is also sensitive to outliers and noise in the data.

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