Unlock the full potential of LinkedIn data with our extensive dataset that combines profiles, company information, and job listings into one powerful resource for business decision-making, strategic hiring, competitive analysis, and market trend insights. This all-encompassing dataset is ideal for professionals, recruiters, analysts, and marketers aiming to enhance their strategies and operations across various business functions. Dataset Features

Profiles: Dive into detailed public profiles featuring names, titles, positions, experience, education, skills, and more. Utilize this data for talent sourcing, lead generation, and investment signaling, with a refresh rate ensuring up to 30 million records per month. Companies: Access comprehensive company data including ID, country, industry, size, number of followers, website details, subsidiaries, and posts. Tailored subsets by industry or region provide invaluable insights for CRM enrichment, competitive intelligence, and understanding the startup ecosystem, updated monthly with up to 40 million records. Job Listings: Explore current job opportunities detailed with job titles, company names, locations, and employment specifics such as seniority levels and employment functions. This dataset includes direct application links and real-time application numbers, serving as a crucial tool for job seekers and analysts looking to understand industry trends and the job market dynamics.

Customizable Subsets for Specific Needs Our LinkedIn dataset offers the flexibility to tailor the dataset according to your specific business requirements. Whether you need comprehensive insights across all data points or are focused on specific segments like job listings, company profiles, or individual professional details, we can customize the dataset to match your needs. This modular approach ensures that you get only the data that is most relevant to your objectives, maximizing efficiency and relevance in your strategic applications. Popular Use Cases

Strategic Hiring and Recruiting: Track talent movement, identify growth opportunities, and enhance your recruiting efforts with targeted data. Market Analysis and Competitive Intelligence: Gain a competitive edge by analyzing company growth, industry trends, and strategic opportunities. Lead Generation and CRM Enrichment: Enrich your database with up-to-date company and professional data for targeted marketing and sales strategies. Job Market Insights and Trends: Leverage detailed job listings for a nuanced understanding of employment trends and opportunities, facilitating effective job matching and market analysis. AI-Driven Predictive Analytics: Utilize AI algorithms to analyze large datasets for predicting industry shifts, optimizing business operations, and enhancing decision-making processes based on actionable data insights.

Whether you are mapping out competitive landscapes, sourcing new talent, or analyzing job market trends, our LinkedIn dataset provides the tools you need to succeed. Customize your access to fit specific needs, ensuring that you have the most relevant and timely data at your fingertips.

Full profile of 10,000 people in the US - download here, data schema here, with more than 40 data points including - Full Name - Education - Location - Work Experience History and many more!

There are additionally 258+ Million US people profiles available, visit the LinkDB product page here.

Our LinkDB database is an exhaustive database of publicly accessible LinkedIn people and companies profiles. It contains close to 500 Million people and companies profiles globally.

LinkedIn data will be a strong resource for businesses and marketers. Such data is useful as it consists of user profiles, job titles, and company information. LinkedIn is a platform that has around 900 million users around the globe, making this one of the largest networks available. With this material, you can create specific campaigns that speak to professionals. You can take advantage of this database because it is kept fresh, which means it still has corrected contacts and individuals. You are using LinkedIn data that gives you access to business decision-makers and industry leaders. Incorporating this dataset into your marketing plan allows you to consolidate outreach efforts. Find your LinkedIn datasets and revamp your outreach strategy at List To Data! LinkedIn number database assists in reaching the target audience and building relationships; this directory provides you with vital information, including contact and user profiles. An essential database, particularly for B2B marketers. You will have access to a comprehensive list of all the LinkedIn members. By using this data, you can better customize your messaging and increase response rates. Furthermore, this resource is updated often, giving your campaigns access to new leads. You may make your outreach efforts more efficient by using this dataset in your marketing strategy. To improve your B2B marketing success and gain access to premium LinkedIn number databases, visit List To Data!

The global number of LinkedIn users in was forecast to continuously increase between 2024 and 2028 by in total ***** million users (+**** percent). After the sixth consecutive increasing year, the LinkedIn user base is estimated to reach ****** million users and therefore a new peak in 2028. User figures, shown here with regards to the platform LinkedIn, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to *** countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of LinkedIn users in countries like Asia and South America.

The LinkedIn posts dataset is a comprehensive collection of user-generated content on LinkedIn, featuring key fields such as post ID, user ID, URL, title, post text, date posted, hashtags, and engagement metrics like the number of likes and comments. This dataset also includes additional elements such as embedded links, images, videos, top visible comments, and links to more posts by the user or relevant content. It is ideal for social media analysts, marketers, and researchers looking to analyze user behavior, content trends, and engagement on LinkedIn.

Success.ai’s User Profiles Data for Nonprofit and NGO Leaders provides businesses, organizations, and researchers with comprehensive access to global leaders in the nonprofit and NGO sectors. With data sourced from over 700 million verified LinkedIn profiles, this dataset includes actionable insights and contact details for executives, program managers, administrators, and decision-makers. Whether your goal is to partner with nonprofits, support global causes, or conduct research into social impact, Success.ai ensures your outreach is backed by accurate, enriched, and continuously updated data.

Why Choose Success.ai’s User Profiles Data for Nonprofit and NGO Leaders? Comprehensive Professional Profiles

Access verified LinkedIn profiles of nonprofit leaders, NGO managers, program directors, grant writers, and administrative executives. AI-driven validation ensures 99% accuracy for efficient communication and minimized bounce rates. Global Coverage Across Nonprofit Sectors

Includes profiles from nonprofits, humanitarian organizations, environmental groups, social enterprises, and advocacy organizations. Covers key markets across North America, Europe, APAC, South America, and Africa for global reach. Continuously Updated Dataset

Reflects real-time professional updates, organizational changes, and emerging trends in the nonprofit landscape to keep your targeting relevant and effective. Tailored for Nonprofit Insights

Enriched profiles include work histories, organizational affiliations, areas of expertise, and social impact projects for deeper engagement opportunities. Data Highlights: 700M+ Verified LinkedIn Profiles: Access a vast network of nonprofit and NGO professionals worldwide. 100M+ Work Emails: Direct communication with executives, managers, and decision-makers in the nonprofit sector. Enriched Organizational Data: Gain insights into leadership structures, mission focuses, and operational scales. Industry-Specific Segmentation: Target nonprofits focused on healthcare, education, environmental sustainability, human rights, and more. Key Features of the Dataset: Nonprofit and NGO Leader Profiles

Identify and connect with executives, program managers, fundraisers, and policy directors in global nonprofit and NGO sectors. Engage with individuals who drive decision-making and operational strategies for impactful organizations. Detailed Organizational Insights

Leverage firmographic data, including organizational size, mission, regional activity, and funding sources, to align with specific nonprofit goals. Advanced Filters for Precision Targeting

Refine searches by region, mission type, role, or organizational focus for tailored outreach. Customize campaigns based on social impact priorities, such as climate action, gender equality, or economic development. AI-Driven Enrichment

Enhanced datasets provide actionable insights into professional accomplishments, partnerships, and leadership achievements for targeted engagement. Strategic Use Cases: Partnership Development and Outreach

Identify nonprofits and NGOs for collaboration on social impact projects, sponsorships, or grant distribution. Build relationships with decision-makers driving advocacy, fundraising, and community initiatives. Donor Engagement and Fundraising

Target nonprofit leaders responsible for managing fundraising campaigns and donor relationships. Tailor outreach efforts to align with specific causes and funding priorities. Research and Analysis

Analyze leadership trends, mission focuses, and regional nonprofit activities to inform program design and funding strategies. Use insights to evaluate the effectiveness of social impact initiatives and partnerships. Recruitment and Talent Acquisition

Target HR professionals and administrators seeking qualified staff, consultants, or volunteers for nonprofits and NGOs. Offer talent solutions for specialized roles in program management, advocacy, and administration. Why Choose Success.ai? Best Price Guarantee

Access industry-leading, verified User Profiles Data at unmatched pricing to ensure your campaigns are cost-effective and impactful. Seamless Integration

Easily integrate verified nonprofit data into your CRM or marketing platforms with APIs or downloadable formats. AI-Validated Accuracy

Rely on 99% accuracy to minimize wasted outreach efforts and maximize engagement outcomes. Customizable Solutions

Tailor datasets to focus on specific nonprofit types, geographical regions, or areas of social impact to meet your strategic objectives. Strategic APIs for Enhanced Campaigns: Data Enrichment API

Update your internal records with verified nonprofit leader profiles to enhance targeting and engagement. Lead Generation API

Automate lead generation for a consistent pipeline of nonprofit and NGO professionals, scaling your outreach efforts efficiently. Success.ai’s User Profiles Data for Nonprofit and NGO Leader...

The dataset contains information on 30,000+ job postings collected from LinkedIn till the year 2023 which provides a rich source of information on job postings on LinkedIn, with concise information on the job title, company, location, and other key attributes of each posting. This data can be used to gain insights into employment trends and dynamics, identify key skills and experiences that are in high demand, and optimize job postings to attract the right candidates.

Taxonomy of the Dataset https://www.googleapis.com/download/storage/v1/b/kaggle-user-content/o/inbox%2F13623947%2F85fde0e9bcd9e6532b63e65ca1e5b58a%2FWhatsApp%20Image%202024-02-27%20at%2012.12.59.jpeg?generation=1709016197299811&alt=media" alt="">

The LinkedIn Jobs Listing dataset emerges as a comprehensive resource for individuals navigating the contemporary job market. With a focus on critical employment details, the dataset encapsulates key facets of job listings, including titles, company names, locations, and employment specifics such as seniority levels and functions. This wealth of information is instrumental for job seekers looking to align their skills and aspirations with the right opportunities. The inclusion of direct application links and real-time application numbers enhances the dataset's utility, offering users a streamlined approach to engaging with potential employers. Beyond aiding job seekers, the dataset serves as a valuable tool for analysts and researchers, providing nuanced insights into industry trends and the evolving demands of the job market. The temporal aspect, captured through job posting timestamps, allows for the observation of job trends over time. Moreover, the dataset's integration of company details, including unique identifiers and LinkedIn profile links, enables a deeper exploration of hiring organizations. Whether for job seekers or analysts, the LinkedIn Jobs Listing dataset emerges as a versatile and informative repository, empowering users with the knowledge to make informed decisions in their professional pursuits.

As of early 2025, LinkedIn had an audience reach of *** million users in the *************. The country was by far the leading market of the professional job networking service, with runner-up India having an audience of *** million. LinkedIn: the company Launched in 2003, LinkedIn is a professional networking service where jobseekers can post their CVs, and employers or recruiters can post job ads and search for prospective candidates. In December 2016, Microsoft acquired LinkedIn, making it a wholly owned subsidiary. In 2020, the platform generated over ***** billion U.S. dollars in revenue. Despite its great success, the company has not always seen positive numbers only, and in 2018, LinkedIn reported an operating loss of *** million U.S. dollars. LinkedIn marketing Greater exposure, lead generation and increased thought leadership are all key benefits of social media marketing, and LinkedIn is a popular marketing tool in the B2B segment. Whereas the company predominantly generates revenue by selling access to member information to professional parties, LinkedIn is the second-most popular social media platform used by B2B marketers, ranking only behind Facebook.

The number of LinkedIn users in the United Kingdom was forecast to continuously increase between 2024 and 2028 by in total 1.5 million users (+4.51 percent). After the eighth consecutive increasing year, the LinkedIn user base is estimated to reach 34.7 million users and therefore a new peak in 2028. User figures, shown here with regards to the platform LinkedIn, have been estimated by taking into account company filings or press material, secondary research, app downloads and traffic data. They refer to the average monthly active users over the period and count multiple accounts by persons only once.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).

LinkedIn user email list is a valid set of database. It can be your most valuable asset in business-to-business marketing and professional networking. An email list of LinkedIn users gives you direct access to a carefully selected group of professionals who are actively involved in their professions and industries. This list, in contrast to standard email lists, comes from the largest professional network in the world. Ensuring that each contact has a verified professional profile.

LinkedIn user email list can be a smart move to target outreach, generate leads, and build meaningful professional relationships. It lets you connect directly with key decision-makers and influencers in your target industry. Bypassing traditional marketing channels that are frequently less effective. Your marketing efforts will be more effective and highly relevant to the recipients as a result of this precision, which will improve engagement and boost conversion rates. LinkedIn user email database takes your marketing capabilities to the next level. Whereas a list provides contact information. Not only does this extensive database contain email addresses. It also contains important information like job titles, company names, industries, seniority levels, and geographical locations. This depth of information transforms a simple email list into a powerful tool for segmentation and personalization. With a robust LinkedIn database. You can craft highly specific and personalized campaigns that speak directly to the needs and interests of your audience. A well-structured database gives you the ability to precisely tailor your message to C-level executives in the tech industry. Again, marketing managers in the retail industry, significantly increasing the effectiveness also.

From the LinkedIn users who identify themselves in the “computer software” industry on their profile and listed at least two skills, we sample about 340,000 users and their skills. To remove skills that are too rare or erroneously typed, we dropped skills appeared less than 100 times in our dataset. # skill_count.tsvThis file contains the frequency of each skill. The first column is the name of the skill; The second column is the number of users who listed the skill; the third column is the total number of users in our dataset. # skill_pair_count.tsv This file contains the co-occurrence between each pair of skills.The first two columns are skill names and the third column is the frequency of co-occurrences.

Salutary Data is a boutique, B2B contact and company data provider that's committed to delivering high quality data for sales intelligence, lead generation, marketing, recruiting, employee data / HR, identity resolution, and ML / AI. Our database currently consists of 148MM+ highly curated B2B Contacts ( US only), along with over 4M+ companies, and is updated regularly to ensure we have the most up-to-date information.

We can enrich your in-house data ( CRM Enrichment, Lead Enrichment, etc.) and provide you with a custom dataset ( such as a lead list) tailored to your target audience specifications and data use-case. We also support large-scale data licensing to software providers and agencies that intend to redistribute our data to their customers and end-users.

What makes Salutary unique? - We offer our clients a truly unique, one-stop aggregation of the best-of-breed quality data sources. Our supplier network consists of numerous, established high quality suppliers that are rigorously vetted. - We leverage third party verification vendors to ensure phone numbers and emails are accurate and connect to the right person. Additionally, we deploy automated and manual verification techniques to ensure we have the latest job information for contacts. - We're reasonably priced and easy to work with.

Products: API Suite Web UI Full and Custom Data Feeds

Services: Data Enrichment - We assess the fill rate gaps and profile your customer file for the purpose of appending fields, updating information, and/or rendering net new “look alike” prospects for your campaigns. ABM Match & Append - Send us your domain or other company related files, and we’ll match your Account Based Marketing targets and provide you with B2B contacts to campaign. Optionally throw in your suppression file to avoid any redundant records. Verification (“Cleaning/Hygiene”) Services - Address the 2% per month aging issue on contact records! We will identify duplicate records, contacts no longer at the company, rid your email hard bounces, and update/replace titles or phones. This is right up our alley and levers our existing internal and external processes and systems.

Job Postings Data for Talent Acquisition, HR Strategy & Market Research Canaria’s Job Postings Data product is a structured, AI-enriched dataset that captures and organizes millions of job listings from leading sources such as Indeed, LinkedIn, and other recruiting platforms. Designed for decision-makers in HR, strategy, and research, this data reveals workforce demand trends, employer activity, and hiring signals across the U.S. labor market and enhanced with advanced enrichment models.

The dataset enables clients to track who is hiring, what roles are being posted, which skills are in demand, where talent is needed geographically, and how compensation and employment structures evolve over time. With field-level normalization and deep enrichment, it transforms noisy job listings into high-resolution labor intelligence—optimized for strategic planning, analytics, and recruiting effectiveness.

Use Cases: What This Job Postings Data Solves This enriched dataset empowers users to analyze workforce activity, employer behavior, and hiring trends across sectors, geographies, and job categories.

Talent Acquisition & HR Strategy • Identify hiring trends by industry, company, function, and geography • Optimize job listings and outreach with enriched skill, title, and seniority data • Detect companies expanding or shifting their workforce focus • Monitor new roles and emerging skills in real time

Labor Market Research & Workforce Planning • Visualize job market activity across cities, states, and ZIP codes • Analyze hiring velocity and job volume changes as macroeconomic signals • Correlate job demand with company size, sector, or compensation structure • Study occupational dynamics using AI-normalized job titles • Use directional signals (job increases/declines) to anticipate market shifts

HR Analytics & Compensation Intelligence • Map salary ranges and benefits offerings by role, location, and level • Track high-demand or hard-to-fill positions for strategic workforce planning • Support compensation planning and headcount forecasting • Feed job title normalization and metadata into internal HRIS systems • Identify talent clusters and location-based hiring inefficiencies

What Makes This Job Postings Data Unique

AI-Based Enrichment at Scale • Extracted attributes include hard skills, soft skills, certifications, and education requirements • Modeled predictions for seniority level, employment type, and remote/on-site classification • Normalized job titles using an internal taxonomy of over 50,000 unique roles • Field-level tagging ensures structured, filterable, and clean outputs

Salary Parsing & Compensation Insights • Parsed salary ranges directly from job descriptions • AI-based salary predictions for postings without explicit compensation • Compensation patterns available by job title, company, and location

Deduplication & Normalization • Achieves approximately 60% deduplication rate through semantic and metadata matching • Normalizes company names, job titles, location formats, and employment attributes • Ready-to-use, analysis-grade dataset—fully structured and cleansed

Company Matching & Metadata • Each job post is linked to a structured company profile, including metadata • Records are cross-referenced with LinkedIn and Google Maps to validate company identity and geography • Enables aggregation at employer or location level for deeper insights

Freshness & Scalability • Updated hourly to reflect real-time hiring behavior and job market shifts • Delivered in flexible formats (CSV, JSON, or data feed) and customizable filters • Supports segmentation by geography, company, seniority, salary, title, and more

Who Uses Canaria’s Job Postings Data • HR & Talent Teams – to benchmark roles, optimize pipelines, and compete for talent • Consultants & Strategy Teams – to guide clients with labor-driven insights • Market Researchers – to understand employment dynamics and job creation trends • HR Tech & SaaS Platforms – to power salary tools, job market dashboards, or recruiting features • Economic Analysts & Think Tanks – to model labor activity and hiring-based economic trends • BI & Analytics Teams – to build dashboards that track demand, skill shifts, and geographic patterns

Summary Canaria’s Job Postings Data provides an AI-enriched, clean, and analysis-ready view of the U.S. job market. Covering millions of listings from Indeed, LinkedIn, other job boards, and ATS sources, it includes detailed job attributes, inferred compensation, normalized titles, skill extraction, and employer metadata—all updated hourly and fully structured.

With deep enrichment, reliable deduplication, and company matchability, this dataset is purpose-built for users needing workforce insights, market trends, and strategic talent intelligence. Whether you're modeling skill gaps, benchmarking compensation, or visualizing hiring momentum, this dataset provides a complete toolkit for HR and labor intelligence.

About Canaria Inc. ...

ChessRender360 is a synthetically crafted dataset featuring 10,000 rendered chess positions. Designed for computer vision and machine learning research, this dataset provides a rich collection of RGB images, depth maps, instance masks, and semantic segmentation masks for each chess piece and board element.

Each chess position is rendered in high resolution (2000x2000 pixels), capturing the intricate details of the board and pieces from various angles. The dataset includes:

• RGB Images: High-quality rendered images of chess positions, showcasing a diverse range of board configurations.
• Depth Maps: Accurate depth representations of the scene, capturing depth in the range of 20 cm to 120 cm. In the depth maps, black corresponds to a depth of 20 cm, and white corresponds to 120 cm, providing spatial information for each position.
• Instance Masks: Unique instance masks for each chess piece, enabling precise identification and localization.
• Semantic Segmentation Masks: Segmentation masks that differentiate between piece types and board elements, with distinct hue values assigned to each type.
• Bounding Boxes: Each sample has an annotation .json file containing bounding boxes for each piece.
• Board Corners: Same annotation .json contains positions of corners of the board in order: white left, white right, black left, black right.
• Pieces Positions: Every piece position is saved in the annotation .json , both in standard chess notation and (row, column) format (0 indexed).
• FENs: A CSV file containing the FEN (Forsyth-Edwards Notation) for each chess position in the dataset, listed in order. This allows users to easily recognize and replicate the exact board position from any image.

Rendering Details:

• 3D Models and Materials: The dataset uses a consistent set of 3D models for all chess pieces, with three different material/color schemes applied across the dataset, along with random perturbations in material brightness, contrast and saturation to introduce visual variety.
• Camera Angles: Camera angles are randomly selected, with yaw ranging from 0 to 360 degrees and pitch between 30 to 80 degrees, providing diverse perspectives of the chess positions.
• Background Variability: The chessboard is randomly placed on different types of tables, with the floor material randomly sampled to create a variety of backgrounds.
• Lighting: Lighting conditions are randomly generated, adding further diversity and realism to the rendered scenes.

Augmentation Potential:

• The instance and semantic masks can be used to further augment the dataset. Researchers can selectively modify specific parts of the images—such as the board, background, or individual pieces—enabling the creation of new variations and enhancing the dataset's utility for model training and testing.

Mapping:

Refer to the mapping.json file for details on how different pieces and board elements are mapped. The mapping includes:

• Frame: Semantic: 10, Instance: 10
• Board Squares: Semantic: 20, Instance: 20 (white square), 21 (black square)
• Pieces: Semantic: increments of 10 starting from 30, Instance: starting from semantic plus 1 for each instance

Applications: ChessRender360 is ideal for tasks such as object detection, instance segmentation, depth estimation, and scene understanding in synthetic environments. Researchers and developers can leverage this dataset for training and evaluating models in computer vision, robotics, and artificial intelligence.

Dataset Highlights:

• 10,000 uniquely rendered chess positions
• High-resolution images (2000x2000 pixels) with diverse visual characteristics
• Comprehensive annotations with RGB, depth (20 cm to 120 cm), instance, and semantic maps
• FEN notation CSV file for easy position recognition and replication
• Variety introduced through different material schemes and lighting setups
• Randomized camera angles for enhanced perspective diversity
• Potential for further augmentation by modifying specific image components
• Suitable for a wide range of computer vision and AI applications

ChessRender360 offers a rich and versatile dataset for advancing research and development in the field of computer vision, providing a synthetic yet highly realistic environment for model training and testing.

For any questions, feedback, or collaboration opportunities, or if you are interested in custom artificial datasets, please contact me:

• Name: Marko Kojić
• LinkedIn: https://www.linkedin.com/in/mmkoya

I welcome inquiries from researchers, developers, and organizations interested in utilizing or collaborating on artificial datasets.

At source mate, we understand the value of accurate and up-to-date data in today's competitive landscape. Our CVs and B2B Linkedin data are meticulously collected, verified, and updated, ensuring their integrity and relevance.

We gather information from various trusted sources, such as our websites, job boards, professional networks, and career websites, to create a comprehensive database of potential candidates actively seeking employment opportunities.

Here's why our job seeker data sets are unparalleled in the industry:

Comprehensive and Targeted: Our data sets cover a wide range of industries, job titles, locations, and experience levels. Whether you're looking for entry-level professionals, mid-level managers, or specialized experts, we have the data to meet your specific requirements. Our data is highly segmented and customizable, enabling you to target your ideal candidates with precision.

Fresh and Updated: We understand the importance of timely information. Our dedicated team ensures that our job seeker data is regularly updated and refreshed to maintain its accuracy and relevance. This means you'll have access to the latest contact details, job preferences, skills, and qualifications of potential candidates, enabling you to engage with them at the right time and with personalized messaging.

GDPR Compliant: Privacy and data protection are paramount to us. We strictly adhere to the General Data Protection Regulation (GDPR) guidelines, ensuring that all data we provide is collected and processed lawfully and ethically. We respect the privacy rights of individuals and maintain the highest standards of data security and confidentiality.

Easy Integration: Our data sets are provided in a format that is easily integrable with your existing systems and platforms. Whether you want to import the data into your CRM, applicant tracking system, or any other software, our user-friendly formats facilitate seamless integration, saving you time and effort.

Reliable Customer Support: We pride ourselves on delivering exceptional customer service. Our dedicated support team is available to assist you at every step of the process, from helping you select the right data sets to answering any queries or concerns you may have. We strive to ensure your experience with source mate is smooth, efficient, and successful.

A good DATA is crucial for any business or organization to grow the network. This is because all relevant details about the company and user are stored in the database. Your companies have benefited from using our email database to extract their prospect's details.

It is a well-known fact that LinkedIn gives you the opportunity to expand your business network. You can easily connect with your prospects, directly or through mutual connections, by using search keywords related to their name, company, profile, address, etc. However, we're a leading data provider, with us you do not need to do such a thing. Our Professional's email database contains all the necessary business information from your prospects. There are several ways to access them (especially email addresses and phone numbers).

With our service, you can reach over 69 million records in 200+ countries. Our database is well organized and keeps information easily accessible, so you can use it. Easily increase your sales with reliable LinkedIn data that connects you directly to your goal, here we have worked hard to supply quality, reliable, sustainable email databases.

This dataset was created by Harry Field and contains the labelled images for capturing the game state of a draughts/checkers 8x8 board.

This was a fun project to develop a mobile draughts applciation enabling users to interact with draughts-based software via their mobile device's camera.

The data captured consists of: * White Pieces * White Kings * Black Pieces * Black Kings * Bottom left corner square * Top left corner square * Top right corner square * Bottom right corner square

Corner squares are captured so the board locations of the detected pieces can be estimated.

https://github.com/ShippingTycoon/roboflow-draughts/blob/main/PXL_20210603_093949805_jpg.rf.30e2a64a0a646e8ea8e121727cf0f1ee.jpg?raw=true" alt="Results of Yolov5 model after training with this dataset">

From this data, the locations of other squares can be estimated and game state can be captured. The image below shows the data of a different board configuration being captured. Blue circles refer to squares, numbers refer to square index and the coloured circles refer to pieces. https://github.com/ShippingTycoon/roboflow-draughts/blob/main/pieces.png?raw=true" alt="">

Once game state is captured, integration with other software becomes possible. In this example, I created a simple move suggestion mobile applciation seen working here.

The developed application is a proof of concept and is not available to the public. Further development is required in training the model accross multiple draughts boards and implementing features to add vlaue to the physical draughts game.

The dataset consists of 759 images and was trained using Yolov5 with a 70/20/10 split.

The output of Yolov5 was parsed and filtered to correct for duplicated/overlapping detections before game state could be determined.

I hope you find this dataset useful and if you have any questions feel free to drop me a message on LinkedIn as per the link above.

The dataset contains responses from 440 Moroccan web users and webmasters who completed a structured survey on cybersecurity awareness and HTTPS-related behaviors. The data were collected using Google Forms and distributed widely through active web development and cybersecurity communities on platforms such as Facebook, WhatsApp, and LinkedIn. The dataset includes raw responses, processed data, encoded datasets, clustering outputs, and interpretation reports generated using machine learning techniques and large language models (LLMs). These reports offer detailed assessments and actionable cybersecurity recommendations. This dataset supports the study of real-world HTTPS deployment practices and secure browsing behaviors across different user roles.

Analysis of ‘Deep-NLP’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/samdeeplearning/deepnlp on 12 November 2021.

--- Dataset description provided by original source is as follows ---

What's In The Deep-NLP Dataset?

Sheet_1.csv contains 80 user responses, in the response_text column, to a therapy chatbot. Bot said: 'Describe a time when you have acted as a resource for someone else'. User responded. If a response is 'not flagged', the user can continue talking to the bot. If it is 'flagged', the user is referred to help.

Sheet_2.csv contains 125 resumes, in the resume_text column. Resumes were queried from Indeed.com with keyword 'data scientist', location 'Vermont'. If a resume is 'not flagged', the applicant can submit a modified resume version at a later date. If it is 'flagged', the applicant is invited to interview.

What Do I Do With This?

Classify new resumes/responses as flagged or not flagged.

There are two sets of data here - resumes and responses. Split the data into a train set and a test set to test the accuracy of your classifier. Bonus points for using the same classifier for both problems.

Good luck.

Acknowledgements

Thank you to Parsa Ghaffari (Aylien), without whom these visuals (cover photo is in Parsa Ghaffari's excellent LinkedIn article on English, Spanish and German postive v. negative sentiment analysis) would not exist.

There Is A 'deep natural language processing' Kernel. I will update it. I Hope You Find It Useful.

You can use any of the code in that kernel anywhere, on or off Kaggle. Ping me at @_samputnam for questions.

--- Original source retains full ownership of the source dataset ---