Knowledge Hut

JANUARY 19, 2024

Entering the world of data science is a strategic move in the 21st century, known for its lucrative opportunities. With businesses relying heavily on data, the demand for skilled data scientists has skyrocketed. Recognizing the growing need for data scientists, institutions worldwide are intensifying efforts to meet this demand.

Data Science 52

Data Science Machine Learning Datasets Algorithm 52

AltexSoft

MAY 12, 2022

Aiming at understanding sound data, it applies a range of technologies, including state-of-the-art deep learning algorithms. Another application of musical audio analysis is genre classification: Say, Spotify runs its proprietary algorithm to group tracks into categories (their database holds more than 5,000 genres ).

Machine Learning 122

Machine Learning Building Datasets Healthcare 122

Knowledge Hut

NOVEMBER 27, 2023

How would one know what to sell and to which customers, based on data? This is where Data Science comes into the picture. Data Science is a field that uses scientific methods, algorithms, and processes to extract useful insights and knowledge from noisy data. Learn about Dataframes, Pandas, and Numpy to begin with.

Data Science 97

Data Science Healthcare Machine Learning Telecommunication 97

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

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. How Does Data Labeling Work?

Machine Learning 52

Machine Learning Process Datasets Raw Data 52

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

Knowledge Hut

JANUARY 22, 2024

Data science is a field of study that combines industry expertise, programming skills, and knowledge of mathematics and statistics to extract meaningful insights from data. Data scientists apply machine learning algorithms to numbers, text, images, video, audio, and more to create artificial intelligence (AI) systems.

Data Science 52

Data Science Banking Big Data Insurance 52

Edureka

AUGUST 2, 2023

Python offers a strong ecosystem for data scientists to carry out activities like data cleansing, exploration, visualization, and modeling thanks to modules like NumPy, Pandas, and Matplotlib. Data scientists can also organize unstructured raw data using SQL so that it can be analyzed with statistical and machine learning methods.

Programming Language 52

Programming Language Programming Scala Pharmaceutical 52

ProjectPro

FEBRUARY 25, 2022

Evolution of Machine Learning Applications in Finance : From Theory to Practice Here are some significant advantages of implementing a data pipeline in machine learning- Efficient Scheduling and Runtime As the machine learning process evolves, you need to repeat many aspects of the machine learning pipeline throughout the organization.

Machine Learning 52

Machine Learning Building Amazon Web Services AWS 52

Knowledge Hut

JUNE 20, 2023

Factors Data Engineer Machine Learning Definition Data engineers create, maintain, and optimize data infrastructure for data. In addition, they are responsible for developing pipelines that turn raw data into formats that data consumers can use easily. When necessary, train and retrain systems.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

ProjectPro

OCTOBER 18, 2021

Machine Learning Projects are the key to understanding the real-world implementation of machine learning algorithms in the industry. Apart from that, libraries like ggplot, reshape2, data.table will complement your machine learning project. Dummy datasets like univariate time-series datasets, shampoo sales datasets, etc.,

Machine Learning 52

Machine Learning Project Datasets Algorithm 52

Knowledge Hut

NOVEMBER 2, 2023

AI systems can minutely analyze existing compositions and generate new musical pieces based on learned patterns. Some of the most common applications of machine learning include: c. While many people have questions like “Is generative AI a type of deep learning?”, How Are They Similar?

Machine Learning 52

Machine Learning Deep Learning Utilities Medical 52

AltexSoft

NOVEMBER 17, 2021

It requires extracting raw data from claims automatically and applying NLP for analysis. Training neural networks and implementing them into your classifier can be a cumbersome task since they require knowledge of deep learning and quite large datasets. Stating categories and collecting training dataset.

Machine Learning 75

Machine Learning Insurance Medical Healthcare 75

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.

Engineering 40

Engineering Deep Learning Software Engineer Software Engineering 40

ProjectPro

JUNE 9, 2021

Data Science- Definition Data Science is an interdisciplinary branch encompassing data engineering and many other fields. Data Science involves applying statistical techniques to raw data, just like data analysts, with the additional goal of building business solutions.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

AltexSoft

MARCH 18, 2022

Supervised vs unsupervised vs semi-supervised machine learning in a nutshell. Supervised learning is training a machine learning model using the labeled dataset. Organic labels are often available in data, but a process may involve a human expert that adds tags to raw data to show a model the target attributes (answers).

Datasets 52

Datasets Machine Learning Algorithm Raw Data 52

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.

Project 40

Project Deep Learning Medical Datasets 40

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.

Hadoop 98

Hadoop Deep Learning Data Science Machine Learning 98

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?

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

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.

Machine Learning 40

Machine Learning Datasets Algorithm Data Science 40

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?

Deep Learning 40

Deep Learning Datasets Machine Learning Algorithm 40

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?

Data Science 40

Data Science Deep Learning NoSQL Machine Learning 40

Knowledge Hut

SEPTEMBER 6, 2023

To obtain a data science certification, candidates typically need to complete a series of courses or modules covering topics like programming, statistics, data manipulation, machine learning algorithms, and data analysis. Python and R are the best languages for Data Science. Expiration - No expiry 5.

Data Science 97

Data Science Certification Business Analyst Machine Learning 97

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

The huge volumes of financial data have helped the finance industry streamline processes, reduce investment risks, and optimize investment portfolios for clients and companies. There is a wide range of open-source machine learning algorithms and tools that fit exceptionally with financial data.

Finance 52

Finance Machine Learning Project Banking 52

Knowledge Hut

JANUARY 18, 2024

It is an interdisciplinary science with multiple approaches, and advancements in Machine Learning and deep learning are creating a paradigm shift in many sectors of the IT industry across the globe. SQL for data migration 2. Python libraries such as pandas, NumPy, plotly, etc.

Data Science 98

Data Science Deep Learning Business Analyst Data Mining 98

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?

Machine Learning 52

Machine Learning Process Raw Data Datasets 52

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

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

U-Next

AUGUST 25, 2022

They will employ the information in Machine Learning models that individuals and organizations may use after they have a deeper knowledge of the raw and different data formats. How Does Machine Learning Work? The subject of Machine Learning cheat sheets is constantly expanding and evolving. Supervised Learning.

Machine Learning 40

Machine Learning Algorithm Data Mining Utilities 40

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

DECEMBER 22, 2016

Data analysis involves data cleaning. Results of data mining are not always easy to interpret. Data analysts interpret the results and convey the to the stakeholders. Data mining algorithms automatically develop equations. Data analysts have to develop their own equations based on the hypothesis.

Data Mining 52

Data Mining Data Cleanse Datasets Data Analysis 52

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. The people who have inquiries about data are known as Data Scientists.

Retail 52

Retail Data Science Computer Science Entertainment 52

ProjectPro

NOVEMBER 30, 2021

The crux of all data-driven solutions or business decision-making lies in how well the respective businesses collect, transform, and store data. When working on real-time business problems, data scientists build models using various Machine Learning or Deep Learning algorithms.

Process 52

Process Data Pipeline Data Warehouse AWS 52

ProjectPro

JANUARY 31, 2022

Databricks Snowflake Projects for Practice in 2022 Dive Deeper Into The Snowflake Architecture FAQs on Snowflake Architecture Snowflake Overview and Architecture With Data Explosion, acquiring, processing, and storing large or complicated datasets appears more challenging. Snowflake offers no built-in virtual private networking.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

AltexSoft

DECEMBER 15, 2021

Machine learning evangelizes the idea of automation. 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. The process of cooking the right food for your algorithm falls into two key steps.

Machine Learning 59

Machine Learning Deep Learning Algorithm Telecommunication 59

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.

Data Mining 52

Data Mining Datasets Machine Learning Metadata 52

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. Calculating the variations between date-column values, etc.

Big Data 52

Big Data Coding Project Hadoop 52