#CodeRevolution
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biographiness ยท 1 year ago
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Unleashing potential, one pixel at a time! ๐Ÿš€๐Ÿ–ฅ๏ธ
Follow๐Ÿ‘‰ @biographiness
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elysiumacademy ยท 1 year ago
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๐ŸŽ‰ Exciting news! ๐ŸŒŸ
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qrdiffusion ยท 2 years ago
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Embrace the QR Art Revolution! ๐ŸŽจ๐Ÿš€ Step into a world where QR codes become masterpieces. With QR Diffusion, make a statement that captivates, intrigues, and inspires!
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stevemartin34 ยท 1 year ago
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๐Ÿš€ ๐„๐ฆ๐›๐ซ๐š๐œ๐ž ๐ญ๐ก๐ž ๐…๐ฎ๐ญ๐ฎ๐ซ๐ž ๐จ๐Ÿ ๐ƒ๐ž๐ฏ๐Ž๐ฉ๐ฌ! ๐Ÿš€
Hey DevOps enthusiasts! ๐ŸŒโœจ Dive into the dynamic world of DevOps evolution and witness the cutting-edge trends shaping the future of software development! ๐Ÿš€๐Ÿ”
๐Ÿ”„ ๐—–๐—ผ๐—ป๐˜๐—ถ๐—ป๐˜‚๐—ผ๐˜‚๐˜€ ๐—œ๐—ป๐˜๐—ฒ๐—ด๐—ฟ๐—ฎ๐˜๐—ถ๐—ผ๐—ป/๐—–๐—ผ๐—ป๐˜๐—ถ๐—ป๐˜‚๐—ผ๐˜‚๐˜€ ๐——๐—ฒ๐—ฝ๐—น๐—ผ๐˜†๐—บ๐—ฒ๐—ป๐˜ (๐—–๐—œ/๐—–๐——):ย  Uncover the magic behind seamless software delivery! Explore the latest advancements in CI/CD pipelines that empower developers to ship code faster and more reliably. ๐Ÿš€๐Ÿ’ป The era of swift, automated releases is here, revolutionizing the way we build and deploy software. ๐ŸŒ๐Ÿš€
๐Ÿ“ฆ ๐—–๐—ผ๐—ป๐˜๐—ฎ๐—ถ๐—ป๐—ฒ๐—ฟ๐—ถ๐˜‡๐—ฎ๐˜๐—ถ๐—ผ๐—ป ๐—ง๐—ฒ๐—ฐ๐—ต๐—ป๐—ผ๐—น๐—ผ๐—ด๐—ถ๐—ฒ๐˜€:๐Ÿค–๐Ÿ”— Enter the realm of containerization and revolutionize the scalability and consistency of your applications! ๐ŸŒ๐Ÿšข Discover how technologies like Docker and Kubernetes are reshaping the deployment landscape, allowing for smoother, more efficient operations. ๐Ÿš€โš™๏ธ
๐ŸŒˆ ๐—ช๐—ต๐˜† ๐——๐—ฒ๐˜ƒ๐—ข๐—ฝ๐˜€?: Understand the pivotal role DevOps plays in fostering collaboration between development and operations teams. ๐Ÿค๐Ÿ’ก It's not just about tools; it's a cultural shift that accelerates innovation and ensures a faster time-to-market. ๐Ÿš€โœจ
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#DevOpsEvolution #CI/CD #Containerization #SoftwareDevelopment #TechInnovation #DevOpsCommunity #CodeRevolution #ContinuousIntegration #ContinuousDeployment #TechTrends #DevOpsJourney
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must-ai-generator ยท 1 year ago
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๐Ÿš€โœจ Unleash Creativity: The Power of Code Writing AI
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Dive into the revolutionary landscape of #CodeWritingAI, #AIWritingCode, #WritingAICode, and #ArtificialIntelligenceWriteCode. Explore the fusion of creativity and technology, reshaping the coding experience. Elevate your coding game with the future of programming! ๐Ÿ’ป๐ŸŒ #CreativeCoding #AIInnovation #CodeRevolution #TechCreativity #ProgrammingPower
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kginfotechthefuture07 ยท 1 year ago
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Embark on a journey of innovation and empowerment! ๐ŸŒ๐Ÿ’ก Join the coding revolution and script your own success story with our transformative coding program. ๐Ÿ’ป๐Ÿš€ Unleash the power of digital empowerment and unlock endless possibilities in the tech world. Ready to shape the future? Enroll now and be part of the #CodeRevolution! #DigitalEmpowerment #TechInnovation #CodingJourney #FutureCoders #TransformativeLearning"
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coderevolution ยท 3 years ago
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dailyzrsworld ยท 4 years ago
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Internet Business Startup Kit Advanced | CodeRevolution
Internet Business Startup Kit Advanced |ย CodeRevolution
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puttoo21 ยท 5 years ago
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Graphical Representation of Progrram :
In the bar charts above we can see the relationship between quantity of joints smoked per month by cannabis user, aged 18 to 30 years old, and both major depression (first) and general anxiety (second) diagnoses in the last 12 months (Q->C). The explanatory variable is quantity of joints (quantitative), while the response variables are depression and anxiety diagnoses (categorical). There is a slightly increasing trend in the first graph, but not in the second. In the graphs presented above we can see the correlation between frequency of cannabis use and both major depression and general anxiety (C->C). The explanatory variable is frequency of cannabis use (categorical), while the response variables are depression and anxiety diagnoses (categorical). Again, for the first graph we have a right-skewed distribution, which indicates that the more an individual smoked cannabis, the better were the chances to get diagnosed with depression. However, we cannot support the same as far as anxiety is concerned, which appears to have a more raffle and abnormal distribution.In the final assignment are presented visualized data, taken from NESARC codebook, in order to examine the correlation between cannabis use and mental disorders such as major depression and general anxiety diagnosed in the last 12 months in a sample of 9535 U.S. young adults, aged from 18 to 30 years old. I used Spyder IDE to create both univariate and bivariate bar charts for the selected variables. More specifically, with variable โ€˜AGEโ€™ between 18 and 30, I built unvariate graphs for categorical variables โ€˜S3BQ1A5โ€™ which represents cannabis use, โ€˜S3BD5Q2Eโ€™ which is frequency of this use, โ€˜MAJORDEP12โ€™ that stands for major depression diagnosis in the last 12 months and โ€˜GENAXDX12โ€™ that indicates general anxiety diagnosis in the same period. In addition, you will find another univariate graph for the quantitative variable โ€˜NUMJOPMOTH_ESTโ€™, which I created in my previous assignment by multiplying frequency of cannabis use and average quantity of joints smoked, in order to estimate the total number of joints smoked per month by the individuals. As far as the bivariate graphs are concerned, I chose to examine visualized the association between cannabis use (C->C) and both mentioned disorders and additionally the relationship between frequency (C->C) and quantity (Q->C) of this use with both depression and anxiety. Thus, bar charts were created combining variables โ€˜S3BQ1A5โ€™ (cannabis use), โ€˜S3BD5Q2Eโ€™ (frequency of use) and โ€˜NUMJOPMOTH_ESTโ€™ (quantity of joints) with variables โ€˜MAJORDEP12โ€™ (major depression) and โ€˜GENAXDX12โ€™ (general anxiety). Concluding, for the quantitative variable both center and spread were measured and describe function was used in order to examine useful information, about the selected categorical variables.
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A random sample of 9535 U.S. young adults, aged 18-30, were asked, as a part of NESARC survey, the following question: โ€œHave you ever used cannabis?โ€ A percentage of 25.29% (or 7042 individuals) answered โ€œYesโ€, whereas 73.85% (or about 2500 individuals) answered โ€œNoโ€ which was the most frequent answer. Also a significantly small percentage of 0.84%, fell into category 9 (โ€œUnknownโ€œ) which is our missing data.ย ย 
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To the question of โ€œHow often did you use cannabis when using the most?โ€, the top answer was โ€œEvery dayโ€, since 534 individuals fell into this category, followed by โ€œOnce a yearโ€ category with approximately 400 individuals. Less than 100 people chose โ€œ7-11 times per yearโ€ category, which was the least frequent answer.
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Of the total number of participants (18-30) who answered โ€œYesโ€ to the question of cannabis use, only those who were smoking marijuana in last 12 months and prior were taken into consideration for the next two questions.
To the question of โ€œHave you been diagnosed with non-hierarchical major depression in the last 12 months?โ€, about 660 participants or 79.04% answered โ€œNoโ€ which was the most frequent answer, whereas 175 or 20.95% fell into โ€œYesโ€.
For the question, โ€Have you been diagnosed with non-hierarchical generalized anxiety in the last 12 months?โ€, 802 individuals or 96.04% answered โ€œNoโ€œ that was our top answer, while only 33 or 3.95% chose โ€œYesโ€œ.
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For the estimated number of joints smoked per month by cannabis users, ages 18-30, it noticeable from the graph that there was a skewed-right distribution. The spread or the standard deviation of the variable is extremely large which indicates a large variety of answers among the participants. The three main numerical measures of the center of the distribution are the mode, the median, and the mean. Here we can see that mode is equal to 0.1 and it was the most common occurring value in the distribution, which means that most of participants smoked less than 1 joint per month. The mean is equal to 70.1 which indicates that cannabis users smoked about 70 joints per month on average and the median or the middle value is 6.
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Estimated number of joints smoked per month binned to groups as illustrated above. Another way of visualizing the distribution of variable โ€˜NUMJOPMOTH_ESTโ€™. We can see that most individuals, about 990, smoked less than one joint per month and the shape of the distribution is right-skewed.
Bivariate graphs:
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In the bar charts above we can see the relationship between quantity of joints smoked per month by cannabis user, aged 18 to 30 years old, and both major depression (first) and general anxiety (second) diagnoses in the last 12 months (Q->C). The explanatory variable is quantity of joints (quantitative), while the response variables are depression and anxiety diagnoses (categorical). There is a slightly increasing trend in the first graph, but not in the second.ย 
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In the graphs presented above we can see the correlation between frequency of cannabis use and both major depression and general anxiety (C->C). The explanatory variable is frequency of cannabis use (categorical), while the response variables are depression and anxiety diagnoses (categorical). Again, for the first graph we have a right-skewed distribution, which indicates that the more an individual smoked cannabis, the better were the chances to get diagnosed with depression. However, we cannot support the same as far as anxiety is concerned, which appears to have a more raffle and abnormal distribution.
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The graphs presented above illustrate the association between cannabis use and both major depression and general anxiety diagnoses in young adults, aged from 18 to 30 years old, in the last 12 months (C->C). The explanatory variable is cannabis use (categorical) and the response variables are depression and anxiety diagnoses (categorical).
SUMMARY :
To sum up, looking through the the last graphs, it can be noticed that there are some slight differences between the percentages of cannabis users compared to non-users. Major depression cases in cannabis users young adults (20.95%) seem to be slightly more than double compared to those of non-users (8.42%).In addition, general anxiety diagnoses in cannabis users (3.95%) appear to be also marginally more than double in comparison to the non-users (1.63%). It could be supported that there is a relative association between cannabis and such mental disorders, thus cannabis use increases the likelihood of meeting criteria for depression or general anxiety in the future. However, the sample is extremely small and it is unclear how representative it is, making the findings less reliable, since a large amount of error may be involved.
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trendapps ยท 5 years ago
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Mega WordPress 'All-My-Items' Bundle by CodeRevolution 6.6 NULLED
Mega WordPress 'All-My-Items' Bundle by CodeRevolution 6.6ย NULLED
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qrdiffusion ยท 2 years ago
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Artistry Meets Functionality! ๐Ÿ–Œ๏ธ๐Ÿ” With QR Diffusion, your QR codes become works of art. Blend creativity and purpose seamlessly, making your codes both visually appealing and highly functional.
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coderevolution ยท 6 years ago
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We work writing great content for our blogs and to be honest, it can suck if we don't get the traffic we deserve (or that we need to earn a decent income!). It feels like a vicious cycleโ€ฆyou can't get the traffic without doing the work, but it's tough to justify all the work if you aren't getting ... http://bit.ly/2QlmPOs
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coderevolution ยท 3 years ago
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coderevolution ยท 3 years ago
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coderevolution ยท 3 years ago
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The Ultimate Anime Scraper plugin was updated, now it can also use Amazon S3 cloud storage for the scraped anime episodes. For more info, watch this video! G... https://l.facebook.com/l.php?u=https%3A%2F%2Fwww.youtube.com%2Fwatch%3Fv%3DorGp4RdNFY4%26feature%3Dyoutu.be&h=AT3RsIEFenNN7fGtrR6c6ka_1YJvQGAvcO7QW7uoROLi44-1rghhWaUP-hfHwwRx32aj0MfUDbtkP5EGbMds9DRoeYQ7I06zDyKvvqWd8fyKwVuGxN9LLt8jxtl0MB2-jWpRXnYptH1EcmUsT_es&s=1
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