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Explore AI generated designs, images, art and prompts by top community artists and designers.
create an image... sleek business card design for a memory foam company , modern typography , soft colors with calming tones , showcasing the luxury and comfort of polyurethane memory foam , delicate textures , minimalist layout , high-quality materials illustration , eye-catching logo positioned prominently , elegant and professional aesthetic , emphasis on innovation and quality craftsmanship , suitable for upscale branding , stylish presentation , inviting feel , ultra-detailed and visually appealing , effective for marketing purposes. ,
an asian woman in front of rice fields , palm trees and mountains with her back to the camera a , looking_at_viewer , long_hair , black_hair , bare_shoulders , jewellery , underwear , standing , panties , ass , earrings , outdoors , parted_lips , solo_focus , day , looking_back , dark_skin , from_behind , dark-skinned_female , tree , lips , crop_top , back , nature , armlet , forest , thong , realistic , bracer ,
A 152cm tall , 41kg petite 23 year old chinese girl with a cute and innocent appearance. She has black eyes , a round face , and a small nose with full lips. Her hair is natural black , styled in twin tails or high ponytails. She has a B-cup chest , a waist (58cm) , and a large buttocks (95cm). She is wearing a White lace underwear and panties. The style is cute and pure。the whole body ,
A 152cm tall , 41kg petite 23 year old chinese girl with a cute and innocent appearance. She has black eyes , a round face , and a small nose with full lips. Her hair is natural black , styled in twin tails or high ponytails. She has a B-cup chest , a waist (58cm) , and a large buttocks (95cm). She is wearing a White lace underwear and panties. The style is cute and pure。the whole body ,
A full-body vertical composition of a divine woman ascending gracefully , her entire figure enveloped in a majestic turquoise mantle that flows dynamically around her , the undisputed centerpiece of the artwork. The mantle , rich in hyperrealistic texture and intricate folds , shimmers with subtle iridescent highlights , inspired by classical Renaissance depictions of ascending virgins yet reimagined with a striking modernist flair. Her pose is ethereal and uplifting , with the mantle billowing as if lifted by an unseen force , revealing glimpses of her form beneath. Her hands are elegantly posed , perfectly proportioned , with slender fingers and smooth , flawless skin , rendered with exceptional anatomical accuracy and artistic grace. Her face carries a serene yet profound expression , with a piercing , soulful gaze that draws the viewer in. The scene is illuminated by dramatic , celestial light , weaving warm complementary tones of radiant reds and oranges into the cool turquoise , a masterful showcase of colorism and tonalism. Soft beams of light and glowing accents enhance the mantle’s vibrancy and her divine presence. The background is a luminous , dreamlike expanse with subtle sparkles of complementary hues , keeping the focus on her ascending figure. Ultra-detailed rendering , photorealistic quality , exquisite details in the fabric’s weave , her subtle skin texture , and her perfectly crafted hands , a harmonious blend of classical grandeur and avant-garde innovation , vibrant and balanced composition , a timeless masterpiece capturing the full majesty of her ascent. ,
Uma adolescente de 16 anos , alta e esguia , com cabelos pretos e lisos que caem na altura dos ombros. Clara tem um estilo moderno e urbano , vestindo roupas típicas de jovens londrinos: uma jaqueta jeans oversized , calça skinny preta e tênis estilosos. Seu rosto expressa um misto de confiança e carinho pela irmã mais nova. Ela pode estar segurando um celular , como se estivesse fazendo uma chamada de vídeo com Carol , ou posando em um ambiente londrino ao fundo , como uma cafeteria charmosa ou uma rua movimentada." ,
A rugged , muscular steampunk adventurer with a brass-plated mechanical arm , visible gears , and intricate hydraulic systems embedded into his skin , stands tall with an air of authority. His dark leather trench coat is unbuttoned , revealing a fitted vest over his strong frame , while a brass whip , coiled at his side , hints at his command over both man and machine. His piercing green eyes burn with a determined gaze as he leans against a massive , steam-powered automaton , his well-groomed beard giving him a sharp , confident look. His sturdy boots press firmly against the cobblestone streets as steam hisses around him. The industrial city behind him is alive with towering gears , airships floating in the mist , and dark alleys glowing under an intricate network of gas lamps and neon lights. His powerful presence is accentuated by the intricate mechanical elements adorning his form—brass gears turning at his wrist , the hydraulic hum of his arm as he grips his cane with hidden blades. He exudes confidence , resilience , and a mastery of the mechanical world around him , a true product of an era where innovation and ambition drive the course of history. ,
very detailed , facing viewer , short hair , black hair , pale skin , fantasy medieval outfit , realistic portrait of a innocent young teen girl , d&d fantasy character art , highly detailed , digital painting , trending on artstation , pixiv , concept art , sharp focus , illustration , art by Ross Tran and Greg Rutkowski and Walt Disney animation , detailed fantasy background , ,
Fairness means ensuring your analysis doesn't create or reinforce bias. This can be challenging , but if the analysis is not objective , the conclusions can be misleading and even harmful. In this reading , you’re going to explore some best practices you can use to guide your work toward a more fair analysis! Consider fairness Following are some strategies that support fair analysis: Best practice Explanation Example Consider all of the available data Part of your job as a data analyst is to determine what data is going to be useful for your analysis. Often there will be data that isn’t relevant to what you’re focusing on or doesn’t seem to align with your expectations. But you can’t just ignore it; it’s critical to consider all of the available data so that your analysis reflects the truth and not just your own expectations. A state’s Department of Transportation is interested in measuring traffic patterns on holidays. At first , they only include metrics related to traffic volumes and the fact that the days are holidays. But the data team realizes they failed to consider how weather on these holidays might also affect traffic volumes. Considering this additional data helps them gain more complete insights. Identify surrounding factors As you’ll learn throughout these courses , context is key for you and your stakeholders to understand the final conclusions of any analysis. Similar to considering all of the data , you also must understand surrounding factors that could influence the insights you’re gaining. A human resources department wants to better plan for employee vacation time in order to anticipate staffing needs. HR uses a list of national bank holidays as a key part of the data-gathering process. But they fail to consider important holidays that aren’t on the bank calendar , which introduces bias against employees who celebrate them. It also gives HR less useful results because bank holidays may not necessarily apply to their actual employee population. Include self-reported data Self-reporting is a data collection technique where participants provide information about themselves. Self-reported data can be a great way to introduce fairness in your data collection process. People bring conscious and unconscious bias to their observations about the world , including about other people. Using self-reporting methods to collect data can help avoid these observer biases. Additionally , separating self-reported data from other data you collect provides important context to your conclusions! A data analyst is working on a project for a brick-and-mortar retailer. Their goal is to learn more about their customer base. This data analyst knows they need to consider fairness when they collect data; they decide to create a survey so that customers can self-report information about themselves. By doing that , they avoid bias that might be introduced with other demographic data collection methods. For example , if they had sales associates report their observations about customers , they might introduce any unconscious bias the employees had to the data. Use oversampling effectively When collecting data about a population , it’s important to be aware of the actual makeup of that population. Sometimes , oversampling can help you represent groups in that population that otherwise wouldn’t be represented fairly. Oversampling is the process of increasing the sample size of nondominant groups in a population. This can help you better represent them and address imbalanced datasets. A fitness company is releasing new digital content for users of their equipment. They are interested in designing content that appeals to different users , knowing that different people may interact with their equipment in different ways. For example , part of their user-base is age 70 or older. In order to represent these users , they oversample them in their data. That way , decisions they make about their fitness content will be more inclusive. Think about fairness from beginning to end To ensure that your analysis and final conclusions are fair , be sure to consider fairness from the earliest stages of a project to when you act on the data insights. This means that data collection , cleaning , processing , and analysis are all performed with fairness in mind. A data team kicks off a project by including fairness measures in their data-collection process. These measures include oversampling their population and using self-reported data. However , they fail to inform stakeholders about these measures during the presentation. As a result , stakeholders leave with skewed understandings of the data. Learning from this experience , they add key information about fairness considerations to future stakeholder presentations. ,