#data science tools | Explore Tumblr Posts and Blogs

develeran · 30 days

Text

Data Science Lifecycle

What Is Data Science?

Data science is a field of study that combines various disciplines to extract valuable information and useful insights from complex data sets. It involves areas such as mathematics, statistics, computer science, and artificial intelligence, and it is widely applied across different sectors to improve planning and decision-making processes.

Data science professionals, known as data scientists, utilize artificial intelligence, particularly machine learning and deep learning, to develop models and generate predictions through advanced algorithms and methods.

DATA SCIENCE DEFINITION: BASICS OF DATA SCIENCE

What Is Data Science Used for?

Data science is utilized by businesses ranging from large corporations to startups to uncover correlations, patterns, and valuable insights, leading to groundbreaking discoveries. This explains the rapid growth of data science, which is transforming numerous industries. Specifically, data science is applied for intricate data analysis, predictive modeling, recommendation generation, and data visualization.

Complex Data Analysis

Data science facilitates swift and accurate analysis. Equipped with diverse software tools and methodologies, data analysts can efficiently identify trends and patterns within extensive and intricate datasets. This empowers businesses to make informed decisions, whether it involves optimizing customer segmentation or conducting comprehensive market analysis.

Predictive Modeling

Data science enables predictive modeling by identifying data patterns through machine learning techniques. Analysts can anticipate future outcomes with a certain level of accuracy, which proves beneficial in sectors like insurance, marketing, healthcare, and finance where predicting event probabilities is crucial for business success.

Recommendation Generation

Companies like Netflix, Amazon, and Spotify leverage data science and big data to generate personalized recommendations based on user behavior. Data science ensures that users receive content tailored to their preferences and interests, enhancing their overall experience on these platforms.

Data Visualization

Data science contributes to creating data visualizations such as graphs, charts, and dashboards, along with comprehensive reporting. This aids non-technical business leaders and busy executives in comprehending complex information about their business's status easily.

Data Science Tools

Data science professionals rely on a range of tools and programming languages throughout their careers. Here are some popular options used in the field today:

Common Data Science Programming Languages:

Python

R

SQL

C/C++

Popular Data Science Tools:

Apache Spark (data analytics tool)

Apache Hadoop (big data tool)

KNIME (data analytics tool)

Microsoft Excel (data analytics tool)

Microsoft Power BI (business intelligence data analytics and visualization tool)

MongoDB (database tool)

Qlik (data analytics and integration tool)

QlikView (data visualization tool)

SAS (data analytics tool)

Scikit Learn (machine learning tool)

Tableau (data visualization tool)

TensorFlow (machine learning tool)

Read more - Data Science Lifecycle

#data science course #datascience #data science course in thane #data science course in mumbai #Data Science Lifecycle #Data Science Tools

0 notes

industry212 · 4 months

Text

10 Must-Have AI Chrome Extensions for Data Scientists in 2024

Empowering data scientists with Top 10 AI Chrome Extensions

The field of data science demands a toolkit that evolves with the industry's advancements. As we enter 2024, the significance of AI Chrome extensions for data scientists cannot be overstated. This article discusses the top 10 extensions that enable data scientists to enhance productivity and streamline workflows.

Codeium:

Codeium, a versatile tool for programmers, streamlines code efficiency in over 20 languages. Through analysis and optimization, it significantly accelerates program execution, minimizing resource consumption. Whether you're a seasoned coder or a beginner, Codeium proves invaluable in enhancing code performance for quicker results and improved resource management.

EquatIO:

EquatIO transforms mathematical expression creation into a seamless digital experience. Whether typing, handwriting, or using voice dictation, it effortlessly translates thoughts into precise formulas. Compatible with Google Docs, Forms, Slides, Sheets, and Drawings, EquatIO fosters an engaging learning environment, offering advanced features like interactive quizzes and chemistry formula prediction.

Instant Data Scraper:

Instant Data Scraper is a powerful and free browser extension that uses AI for seamless data extraction from any website. No scripting needed; it analyzes HTML structures for relevant data, providing customization options for precision. Ideal for lead generation, SEO, and more, with secure data handling. No spyware, just efficient web scraping.

Challenge Hunt:

Challenge Hunt is your go-to app for staying updated on global programming competitions and hackathons. It covers coding challenges, hackathons, data science competitions, and hiring challenges. Set reminders for upcoming events and personalize your experience by selecting preferred online platforms. Never miss a coding opportunity with this all-in-one competition tracker.

CatalyzeX:

CatalyzeX is a browser extension that revolutionizes how researchers and developers access machine learning implementations. Seamlessly integrated into your web browser, it adds intuitive "[CODE] buttons" to research papers across Google, ArXiv, Scholar, Twitter, and Github. Instantly navigate to open source code, powered by the esteemed CatalyzeX.com repository, unlocking a world of cutting-edge machine learning advancements.

Sider:

Sider is a versatile text processing tool designed to streamline tasks in data science. Whether clarifying complex concepts, translating foreign text, summarizing articles, or rephrasing documents, Sider adapts seamlessly. Its versatility proves invaluable to students, writers, and professionals across academia, business, and technology.

Originality.AI:

Originality.AI is a vital data science tool addressing the challenge of discerning between human and AI-generated text. It accurately identifies authorship, distinguishing content created by humans from that generated by neural networks as AI advances in text creation.

Fireflies:

Fireflies, powered by GPT-4, is an invaluable assistant for data scientists. It excels in navigating and summarizing diverse content types like articles, YouTube videos, emails, and documents. In the era of information overload, Fireflies efficiently sorts and summarizes content from various sources, offering a vital solution for data professionals.

AIPRM:

AIPRM facilitates optimal use of Generative Pretrained Transformers by offering a diverse catalog of well-structured prompts designed for data scientists and IT professionals. With scenarios covering a range of use cases, users can customize GPT model responses to precise requirements, enhancing overall model effectiveness in diverse applications.

Code Squire.AI:

Code Squire.AI is a dedicated code assistant for data science, excelling in Pandas and supporting JupyterLab and Colab. It streamlines coding, reduces errors, and boosts efficiency in data science tasks.

#Data Science #Data Scientist #AI Chrome Extensions #Data Science Tools

0 notes

uncodemytraininginstitute · 6 months

Text

To kickstart a career in Data Science in 2023, focus on building a strong foundation in data analysis, machine learning, and programming, while continuously honing your problem-solving skills. Stay up-to-date with industry trends, seek internships or projects for hands-on experience, and network within the data science community to maximize your career prospects. Read more...

#uncodemy #data science #career in data science #data science tools

1 note · View note

analyticspursuit · 11 months

Text

5 Exciting New Data Science Tools to Check in 2023

Python’s extensive array of data science tools attracts users from all over. However, with such a vast and comprehensive collection, it’s not uncommon for the finest tools to go unnoticed.

Let me walk you through several remarkable data science projects that may have slipped under your radar. While some, such as Polars, have gained increased recognition recently, they still deserve even greater attention. On the other hand, hidden gems like ConnectorX are waiting to be discovered by data enthusiasts like yourself.

This article will introduce you to the exciting realm of new data science tools for 2023.

#data science #data science tools #data science tools 2023 #data scientist #data #data analysis

0 notes

emily-joe · 1 year

Link

BI tools deal with the collection, transformation, and presentation of data. The top business intelligence tools for data visualization are Tableau, Microsoft Power BI, QlikView.

#big data tools #data visualization #business intelligence #data science specialist #data science #data analytics #data science tools

0 notes

rajanarya · 1 year

Text

#Data Science Tools

0 notes

1stepgrow · 1 year

Text

Top Data Science Tools

Data science requires a wide variety of tools. The tools used in data science can be used to analyze data, create attractive interactive and interactive visualizations, as well as create powerful predictive models that use Machine Learning algorithms.

A majority of data science tools provide complex operations for data science all in one place. This makes it simpler for users to use the functions that are associated with data science, without writing their own code from scratch. There are many different tools that are geared toward the various applications that are related to data science.

To become a data scientist to must have knowledge of these tools. The 1stepGrow online course for data science will help you get hands-on training in the most critical tools and technologies. This Data Science course includes 400 hours of intense live training, 25+ projects and 5+ capstone projects. 1stepGrow offers this Data Science course with 100% Job placement.

For more information, please visit: 1stepGrow

#data science #big data #data analytics #data scientist #data visualization #data analysis #data science tools

1 note · View note

usdsi · 2 years

Text

Top 13 Data Visualization Tools for 2023 and Beyond

With the enormity of data, data visualization has become the most sought-after method to depict huge numbers in simpler versions of maps or graphs. Data science tools fed in Data science certification programs are key to any business group, as they hire a Certified Data Scientist to work for their bigger organizational good.

Visit - https://bit.ly/3CoQ0sh

#Data science professionals #Data Science Certification Programs #Data Science Tools #DATA VISUALIZATION TOOLS #USDSI

0 notes

analytics-squad · 2 years

Link

Our data science tool helps you make sense of your data by converting and preparing it for analysis. Analytics Squad has a credible reputation in this regard. Being a specialist in data analysis and having earned a name for itself in the industry for its progressive data analytics, we use an array of data quality tools. Visit our website for more detail.

#data science tools #data science upgrade

0 notes

datasciencecouncil · 2 years

Photo

Top 20 Data Science Platforms & Their Most Common Uses

#data science #data science career #data science certifications #data science tools #data science professional

1 note · View note

womaneng · 8 months

Text

#tools #data scientist #datavisualization #data science

2 notes · View notes

uncodemytraininginstitute · 6 months

Text

The article provides a comprehensive overview of the diverse tools and technologies used in the field of data science, offering insights into the evolving landscape of this dynamic industry. It highlights the essential tools and their applications, facilitating a deeper understanding of data science practices. Read more...

#uncodemy #data science tools #data science technologies #data science #data #noida

0 notes

aboutaiart · 8 months

Text

Know about AI in full detailed.

#machine learning #ai art #popular #ai creativity #artificial intelligence #ai and data science #about ai #ai #art by artificail intelligence #artists on tumblr #digital artist #ai technology #generative ai #ai tools #ai music #ai music composer #ai cover

2 notes · View notes

purple-slate · 10 months

Text

What is Conversational Insights in Under 5 Minutes

What is Conversational Insights?

Conversational insights is a novel approach to analyzing data that uses the natural language of customers, employees, and partners to understand their needs. It allows for better communication, improved insight, and faster decision-making.

Conversational insights is a new way to interact with your business data. It’s more natural and intuitive for users, who can get answers without the added complexities of a query-driven data analytics tool. And it can be used in many industries — from healthcare to manufacturing — to improve productivity and better understand customer needs.

The concept of conversation-driven analytics has been around for some time, but it’s just now starting to gain traction because of its potential as part of the trend toward Natural Language Processing (NLP). This technology is also part of the growing interest in artificial intelligence (AI), which uses computers’ ability to learn from experience or observation rather than being told what to do by programmers or humans telling them how things should work.

Why Do We Need Conversational Insights?

To understand the need for conversational-driven business intelligence platforms, one needs to look at the current suite of self-service analytics tools. They started with the noble intention of enabling everyone to derive contextual stories from data, but have metamorphosed into a form that’s undesirable at large. There are three major shortcomings of the current suite of self-service analytics platforms.

Complexity in Usage: These tools demand a certain degree of expertise that requires training, certifications, and more to use. The difficulty of operating these tools exponentially increases with the amount of data being collected and processed.

Additional Overheads: Specialized teams are employed to create reports when the volume and the level of sophistication surpass the expertise of regular IT teams. This adds to the overheads along with licensing costs.

Time Loss: Even for a seasoned user to create dashboards and reports, will take him or her a specific amount of time. The time loss is directly proportional to the volume of reports.

The impact of shortcomings affects businesses heavily, often resulting in loss of revenue.

Information Overload: An excess of information to make a data-driven decision leads to employee burnout, and failing productivity levels.

Painful Delays in Data Access: Time loss in delivering dashboards coupled with information overload hits the business where it hurts. Taking data-driven time-bound decisions.

Hence it’s imperative to implement a different business intelligence system, one that’s intuitive to how humans access information.

Are there any Benefits in Implementing Conversational Insights?

For decades, the adoption of business intelligence tools has hovered in the range of 20–30% of users in an organization. Business Intelligence systems were used only by a few within the organization and not tapping their full potential. Conversational Insights is designed to improve adoption amongst all data users by encouraging them to access insights in the language they speak.

Introducing intuitive business intelligence platforms to the middle and senior management team or whoever is part of the decision-making, will lead to a manifold increase in the company’s revenue. AI-powered conversational insights enable business users to find information on the go. Ad hoc queries can be resolved quickly by BI teams, taking only a few seconds as opposed to days or weeks. What’s more important is that the system will be able to learn and improve continuously.

Enhanced Returns: Enables business users with actionable insights and allows them to uncover business issues even before they occur

Higher user adoption: A straightforward language-based interface that enables even all users in the organization to use the tools with basic training

Data democratization: Access and understand data without analytical, statistical, or data-handling skills

Improved decision-making: A search-driven analytics platform allows users to dive deeper, discover AI/ML-powered insights, and find the most granular information by allowing them to explore data in any direction

The Future of Business Intelligence will be Conversational

Conversational insights is the future of business intelligence and is here to get the most out of available data and make better decisions. Voice-enabled data analytics help HR managers find the right people, engage with them, and build a relationship before they even decide to hire them. This approach enables sales managers to understand customer emotions and build tailored experiences for them. Supply chain personnel can plan to mitigate the risk of dwindling SKUs and proactively plan effective shipping routes. The applications of a conversational insight tool are endless.

"Intrigued to learn more about conversational insights? Check out our webinar where we discuss the story of how conversational insights is revolutionizing the data analytics industry."