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?

Machine Learning 52

Machine Learning Process Datasets Raw Data 52

Knowledge Hut

NOVEMBER 27, 2023

In fact, you reading this blog is also being recorded as an instance of data in some digital storage. In 2018, the world produced 33 Zettabytes (ZB) of data, which is equivalent to 33 trillion Gigabytes (GB). Learn about Dataframes, Pandas, and Numpy to begin with. It’s a great place to learn Data Science.

Data Science 97

Data Science Healthcare Machine Learning Telecommunication 97

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

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

IT Hospitality Healthcare Deep Learning 52

AltexSoft

DECEMBER 15, 2021

feature engineering or feature extraction when useful properties are drawn from raw data and transformed into a desired form, and. The accuracy of the forecast depends not only on features but also on hyperparameters or internal settings that dictate how exactly your algorithm will learn on a specific dataset.

Machine Learning 59

Machine Learning Deep Learning Algorithm Telecommunication 59

Picnic Engineering

JULY 24, 2023

Want to learn more about why and how we aim to do that utilizing fruit and festive experiments? In this blog post, we’ll discuss how we teach transformers to distinguish between products like a potato and a banana, thereby enhancing future demand prediction. Notably, approximately 20% of the dataset is allocated for evaluation.

Datasets 52

Datasets Architecture Utilities Raw Data 52

ProjectPro

OCTOBER 18, 2021

Apart from that, libraries like ggplot, reshape2, data.table will complement your machine learning project. Datasets like Google Local, Amazon product reviews, MovieLens, Goodreads, NES, Librarything are preferable for creating recommendation engines using machine learning models. for developing these kinds of projects.

Machine Learning 52

Machine Learning Project Datasets Algorithm 52

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.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

ProjectPro

AUGUST 16, 2021

Machine Learning Projects on Classification 2. Machine Learning Projects on Prediction 3. Machine Learning Projects on Computer Vision 4. Machine Learning Projects on Natural Language Processing (NLP) 5. Deep Learning and Neural Network Projects 6.

Machine Learning 40

Machine Learning Coding Project Deep Learning 40

ProjectPro

OCTOBER 27, 2021

Wondering how to implement machine learning in finance effectively and gain valuable insights? 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. Use the Pandas data frame to read and store your data.

Finance 52

Finance Machine Learning Project Banking 52

ProjectPro

JULY 12, 2021

While data science is the most hyped-up career path in the data industry, it certainly isn't the only one. You can consider many other high-paying career options as a data enthusiast. This blog will take you through a relatively new career title in the data industry — AI Engineer.

Engineering 40

Engineering Deep Learning Software Engineer Software Engineering 40

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

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

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?

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

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. To try and predict this, an extensive dataset including anonymised details on the individual loanee and their historical credit history are included. Get the Dataset.

Machine Learning 136

Machine Learning Datasets Data Science Raw Data 136

ProjectPro

FEBRUARY 19, 2021

Image Source: [link] Overfitting : Overfitting happens when the ML model learns the training data such that it memorizes every little detail and noise, making it less generalizable and therefore the model performs badly on any unknown dataset and is ridiculously complex. So, we’ll take an example.

Machine Learning 40

Machine Learning Datasets Algorithm Data Science 40

U-Next

AUGUST 3, 2022

The people who have inquiries about data are known as Data Scientists. Additionally, they must be able to formulate those questions utilising a variety of tools, including analytic, economic, deep learning, and scientific techniques. What are Data Scientist roles? What is the work of a Data Scientist?

Retail 52

Retail Data Science Computer Science Entertainment 52