Data Science Dojo

JULY 3, 2024

Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud. Data Processing and Analysis : Techniques for data cleaning, manipulation, and analysis using libraries such as Pandas and Numpy in Python.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

Pickl AI

SEPTEMBER 24, 2024

This feedback is analysed using natural language processing (NLP) techniques to identify common themes and issues related to service quality. Hadoop Ecosystem As one of the largest Hadoop installations globally, Uber uses this open-source framework for storing and processing vast amounts of data efficiently.

Analytics 52

Analytics Analytics Machine Learning Machine Learning 52

ODSC - Open Data Science

DECEMBER 19, 2023

The most popular programming languages for machine learning include Python, R, and Java. The most popular data science tools include Hadoop, Spark, and Hive. NLP Engineer NLP engineers are responsible for developing and maintaining natural language processing systems.

Data Scientist 96

Data Scientist Machine Learning Machine Learning Computer Science 96

Pickl AI

DECEMBER 2, 2024

Processing frameworks like Hadoop enable efficient data analysis across clusters. Distributed File Systems: Technologies such as Hadoop Distributed File System (HDFS) distribute data across multiple machines to ensure fault tolerance and scalability. Data lakes and cloud storage provide scalable solutions for large datasets.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

NOVEMBER 25, 2024

Processing frameworks like Hadoop enable efficient data analysis across clusters. Distributed File Systems: Technologies such as Hadoop Distributed File System (HDFS) distribute data across multiple machines to ensure fault tolerance and scalability. Data lakes and cloud storage provide scalable solutions for large datasets.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Mlearning.ai

MAY 23, 2023

Check out this course to build your skillset in Seaborn —  [link] Big Data Technologies Familiarity with big data technologies like Apache Hadoop, Apache Spark, or distributed computing frameworks is becoming increasingly important as the volume and complexity of data continue to grow.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

JANUARY 13, 2025

Key Skills Proficiency in programming languages such as Python or Java. Hadoop , Apache Spark ) is beneficial for handling large datasets effectively. They ensure that data is accessible for analysis by data scientists and analysts. Salary Range : 8,00,000 – 25,00,000 per annum. Experience with big data technologies (e.g.,

Machine Learning 52

Machine Learning Machine Learning AI AI 52

AWS Machine Learning Blog

APRIL 19, 2024

The summary describes an image related to the progression of natural language processing and generative AI technologies, but it does not mention anything about particle physics or the concept of quarks. Prior to joining AWS, Archana led a migration from traditional siloed data sources to Hadoop at a healthcare company.

AWS 123

AWS ML ML Database 123

IBM Journey to AI blog

JULY 6, 2023

Today, machine learning has evolved to the point that engineers need to know applied mathematics, computer programming, statistical methods, probability concepts, data structure and other computer science fundamentals, and big data tools such as Hadoop and Hive. Python is the most common programming language used in machine learning.

Machine Learning 70

Machine Learning Machine Learning Data Science Big Data 70

Pickl AI

JULY 20, 2023

5. Text Analytics and Natural Language Processing (NLP) Projects: These projects involve analyzing unstructured text data, such as customer reviews, social media posts, emails, and news articles. To ascertain the general sentiment and deal with any potential problems, use natural language processing (NLP) tools.

Analytics 40

Analytics Analytics Big Data Big Data 40

Pickl AI

JUNE 19, 2024

There are beginner-friendly programs focusing on foundational concepts, while more advanced courses delve into specialized areas like machine learning or natural language processing. Identify your area of interest, whether it’s machine learning, natural language processing, or data visualization.

Data Science 52

Data Science Data Scientist Hypothesis Testing Natural Language Processing 52

Pickl AI

OCTOBER 8, 2024

DFS provides a scalable and efficient way to manage unstructured data across multiple nodes, ensuring that AI applications can access and process large datasets without bottlenecks. This is crucial for tasks such as Natural Language Processing and image recognition, where data diversity and volume are essential.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Algorithm Computer Science 52

ODSC - Open Data Science

JANUARY 7, 2025

Natural Language Processing (NLP) has emerged as a dominant area, with tasks like sentiment analysis, machine translation, and chatbot development leading the way. Hadoop, though less common in new projects, is still crucial for batch processing and distributed storage in large-scale environments.

Data Scientist 40

Data Scientist Data Science Machine Learning Machine Learning 40

Pickl AI

JULY 18, 2023

Additionally, its natural language processing capabilities and Machine Learning frameworks like TensorFlow and scikit-learn make Python an all-in-one language for Data Science. Its speed and performance make it a favored language for big data analytics, where efficiency and scalability are paramount.

Data Science 52

Data Science SQL Data Scientist Python 52

DagsHub

OCTOBER 23, 2024

Popular data lake solutions include Amazon S3 , Azure Data Lake , and Hadoop. Data Processing Tools These tools are essential for handling large volumes of unstructured data. They assist in efficiently managing and processing data from multiple sources, ensuring smooth integration and analysis across diverse formats.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

Pickl AI

NOVEMBER 28, 2024

These networks can learn from large volumes of data and are particularly effective in handling tasks such as image recognition and natural language processing. Key Deep Learning models include: Convolutional Neural Networks (CNNs) CNNs are designed to process structured grid data, such as images.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

Pickl AI

JULY 10, 2023

R’s machine learning capabilities allow for model training, evaluation, and deployment. · Text Mining and Natural Language Processing (NLP): R offers packages such as tm, quanteda, and text2vec that facilitate text mining and NLP tasks.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52

Pickl AI

MAY 31, 2023

Accordingly, there are many Python libraries which are open-source including Data Manipulation, Data Visualisation, Machine Learning, Natural Language Processing , Statistics and Mathematics. It can be easily ported to multiple platforms. It is critical for knowing how to work with huge data sets efficiently.

Data Science 52

Data Science Python Data Scientist Machine Learning 52

DagsHub

NOVEMBER 11, 2024

Social media conversations, comments, customer reviews, and image data are unstructured in nature and hold valuable insights, many of which are still being uncovered through advanced techniques like Natural Language Processing (NLP) and machine learning. This is where artificial intelligence steps in as a powerful ally.

AI 52

AI AI Data Lakes Database 52

Mlearning.ai

AUGUST 18, 2023

Natural Language Processing (NLP) can be used to streamline the data transfer. This technology can process unstructured data, take into account grammar and syntax, and identify the meaning of the information. The issue is that handwritten files often get misplaced or lost.

Data Science 52

Data Science Data Scientist Internet of Things Apache Hadoop 52

Data Science Dojo

MAY 24, 2024

Java is also widely used in big data technologies, supported by powerful Java-based tools like Apache Hadoop and Spark, which are essential for data processing in AI. Big Data Technologies With the growth of data-driven technologies, AI engineers must be proficient in big data platforms like Hadoop, Spark, and NoSQL databases.

Machine Learning 195

Machine Learning Deep Learning Deep Learning Machine Learning 195

Data Science Dojo

AUGUST 30, 2023

Big data processing With the increasing volume of data, big data technologies have become indispensable for Applied Data Science. Technologies like Hadoop and Spark enable the processing and analysis of massive datasets in a distributed and parallel manner.

Data Science 195

Data Science Hypothesis Testing Machine Learning Machine Learning 195

Pickl AI

APRIL 2, 2024

SQL (Structured Query Language): Language for managing and querying relational databases. Hadoop/Spark: Frameworks for distributed storage and processing of big data. Tableau/Power BI: Visualization tools for creating interactive and informative data visualizations.

Data Science 52

Data Science Machine Learning Machine Learning Predictive Analytics 52

Pickl AI

DECEMBER 4, 2024

Enhanced Data Visualisation: Augmented analytics tools often incorporate natural language processing (NLP), allowing users to query data in conversational terms and receive visualised insights instantly. These platforms enable processing of large datasets across distributed computing environments.

Data Science 52

Data Science Data Scientist Machine Learning Machine Learning 52