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MV Analysis/Theory: BTS and Nietzsche
"One must still have chaos within oneself, to give birth to a dancing star." - Thus Spoke Zarathustra: A Book for All and None, by Friedrich Nietzsche. (wiki on the book here) 1. For Whom You Shine The book begins with the quote: "You great star, what would your happiness be had you not those for whom you shine?" This clearly plays into the song lyrics, that they are nothing without the person they love. They offer their blood, sweat and tears to them, without this person to shine for, they are empty. 2. The Most Beautiful Moment in Life Nietzsche's writing often refers to the idea of eternal recurrence. This is the idea that all events in one's life will happen again and again, infinitely. "The embrace of all of life's horrors and pleasures alike shows a deference and acceptance of fate, or Amor Fati. The love and acceptance of one's path in life is a defining characteristic of the overman*. *Overman - Nietzsche thinks that it is important for every generation to overcome their humanity. To be better than it, to push forward and grow and defy the boundaries set by the mere fact that we're human. Someone who creates something new is an overman. Is Jin repeating his actions over and over again but changing it slightly each time? Are we witnessing the butterfly effect? (For example we see Jungkook on the bike again, the lilies from I Need U, etc) Will the most beautiful moment in life go on forever, and is it turning into a nightmare?
when i will get job according to my date of birth
Know Everything about Career Astrology. Such as Career Horoscope Reading, Job Prediction, Promotions, Government Job, when willi buyemployment. What are the varied problems that you simply could be facing in your personal life and professional life? Oronce youwill get your dream job? How quickly will you reach your professional aims? Yourbusiness lifeiscrammed withworries and cares, how quickly will you beable tosmash it, when will i get job You are facing many problems inbusiness lifeand privatelife,you'lllivea far betterlife, find it with career Report or Career consultation today! free career astrology report !! Everyone knows that how important is our career and its importance for stability in life, We are hereto assisttogether with yourcareer andbusiness life, whichisn'tgoing the wayyou would likeand that weare willingto enhanceyour career prospects. A good job helps you in getting both peaceful personal and financial life. But sometimesit isn'tthat easyto requirecare of yourself whilebrowsingthis phase of life, and at some point,you'veto face some ups and downs in your work. Whetheryou are a matured professional, located at a secured jobotherwise yougetan honestamount, With career astrology,you will getanswersto all or anyor any of your personal professional interests and insight into your professional prospects in your forthcoming future. career kundli What Questionsyou'llask? When will you buy a job? Is itan excellent idea to require a replacement job proposal now? Is itan honest approach toa replacementjob offer now ? Why can’t i find a job?the way toaffectit? Which day and time arethe simpleston behalf of mefor appointmentduring anew job opportunity ? I wantto reemployment, but my husbanddoesn'twant meto figure, what should i do? Idon'tlike my jobin the least, howam i able togetthe workof my dream? Willi buyaraisethis year? I have received several job offers. Which one should I choose? I graduated 1-2 years agoand that icannot seemto seek outemploymentin my field. Should Ikeep it uplooking or should I train for something else? Is itan honestopportunityto varymy workplace immediately? I amuninterested insitting home.i would liketo become a fitness instructor. Will I be good at it.? What does my birth chart show about my work atmosphere and career progress this year? What isthe simplest suitable career choice for me? Shouldi'm goingfor business or Job?i'mworking hard but getting no result? why are my effortsgetting intovain? I am battling the work. Is it the proper time to vary the work.
What is Your Chinese Zodiac?
It is believed that the years represented by the animals affect the characters of people in the same way like the western astrology signs! What are your signs?! Rat (쥐 - jwee) Years: 1948, 1960, 1972, 1984, 1996, 2008, 2020 It has characteristics of an animal with spirit, wit, alertness, delicacy, flexibility and vitality. 1984 Liners: Bom (2NE1), Dara (2NE1), Se7en, Simon D (Supreme Team) 1996 Liners: Youngjae (Got7), Zelo (B.A.P.), Lee Hi, Hoshi (Seventeen) Best romantic match: Ox, Rabbit and Dragon Ox (소 - so) Years: 1949, 1961,1973, 1985, 1997, 2009, 2021 They are a symbol of diligence, persistence and honesty. 1985 Liners: Kangin (Super Junior), Shindong (Super Junior) 1997 Liners: BamBam (Got7), Jungkook (BTS)Yugyeom (Got7), Mingyu (Seventeen) Best Romantic Match: Rat, Monkey and Rooster Tiger (호랑이 - ho-rang-ee) Years: 1950, 1962, 1974, 1986, 1998, 2010, 2022 Tigers, considered to be brave, forceful, stately and terrifying, are the symbol of power and lordliness. 1986 Liners: BoA, Changmin (2AM), Donghae (Super Junior), Jaejoong (JYJ) 1998 Liners: Seungkwan (Seventeen), Vernon (Seventeen), Best Romantic Match: Dragon, Horse and Pig Rabbit (토끼 - To-kki) Years: 1951, 1963, 1975, 1987, 1999, 2011, 2023 People in Rabbit sign are not aggressive and approachable. They have a decent, noble and elegant manner. 1987 Liners: Ga-in, Jay Park, TOP, Victoria (f(x)) 1999 Liners: Soohyun (Akdong Musician), Dino (Seventeen) Best Romantic Match: Sheep, Monkey, Dog and Pig Dragon (용 - yohng) Years: 1952, 1964, 1976, 1988, 2000, 2012, 2024 They are the token of authority, dignity, honor, success, luck, and capacity. 1988 Liners: Changmin (TVXQ), G-Dragon, Taecyeon (2PM), Taeyang Best Romantic Match: Rat, Tiger and Snake Snake (뱀 - baem) Years: 1953, 1965, 1977, 1989, 2001, 2013, 2025 Snake carries the meanings of malevolence, cattiness and mystery, as well as acumen and divination. 1989 Liners: Ailee, Junhyung (B2ST), Onew (SHINee), Daesung (Big Bang), Taeyeon Best Romantic Match: Dragon and Rooster Horse (말 - mal) Years: 1954, 1966, 1978, 1990, 2002, 2014, 2026 The animal gives people an impression of independence and integrity, enthusiasm and energy. 1990 Liners: B-Bomb (Block B), Bora (SISTAR), Jonghyun (SHINee), N (VIXX), Yongguk (B.A.P.), Taekwoon (VIXX) Best Romantic Match: Tiger, Sheep and Rabbit Sheep (양 - yang) Years: 1943, 1955, 1967, 1979, 1991, 2003, 2015, 2027 Sheep (goat, or ram) is among the animals that people like most. It is gentle and calm. The white cute creature often reminds people of beautiful things. 1991 Liners: CL, CNU (B1A4), Hoya, Hyorin, Kevin (U-Kiss), Key (SHINee), Sungyeol (Infinite) Best Romantic Match: Rabbit, Horse and Pig Monkey (원숭이 - weon-soong-i) Years: 1944, 1956, 1968, 1980, 1992, 2004, 2016, 2028 The monkey is a clever animal. It is usually compared to a smart person. (It's the year of the monkey this year!) 1992 Liners: Amber, Baekhyun, Baro (B1A4), Chanyeol, Ken (VIXX), Zico Best Romantic Match: Ox and Rabbit Rooster (수탉 - su-talk) Years: 1945, 1957, 1969, 1981, 1993, 2005, 2017, 2029 Rooster is almost the epitome of fidelity and punctuality. 1993 Liners: D.O. (EXO), Daehyun (B.A.P.), Hongbin (VIXX), Mark (Got7), Mino (WINNER), Suga (BTS) Best Romantic Match: Ox and Snake Dog (개 - gae) Years: 1946, 1958, 1970, 1982, 1994, 2006, 2018, 2030 The Chinese regard it as an auspicious animal. If a dog happens to come to a house, it symbolizes the coming of fortune. 1994 Liners: Hyeri (Girls Day), Ilhoon (BTOB), J-Hope (BTS), Jackson (Got7), Krystal (f(x)), Youngjae (B.A.P.) Best Romantic Match: Rabbit Pig (돼지 - dwae-ji) Years: 1947, 1959, 1971, 1983, 1995, 2007, 2019, 2031 It has no calculation to harm others, and can bring affluence to people. Consequently, it has been regarded as wealth. 1995 Liners: Hyuk (VIXX), Jimin (BTS), Jongup (B.A.P.), JR (NUEST), V (BTS), Jeonghan (Seventeen) Best Romantic Match: Tiger, Rabbit and Sheep Whats your sign?!
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New Question A Machine Learning Specialist is building a convolutional neural network (CNN) that will classify 10 types of animals. The Specialist has built a series of layers in a neural network that will take an input image of an animal, pass it through a series of convolutional and pooling layers, and then finally pass it through a dense and fully connected layer with 10 nodes. The Specialist would like to get an output from the neural network that is a probability distribution of how likely it is that the input image belongs to each of the 10 classes. Which function will produce the desired output? A. Dropout B. Smooth L1 loss C. Softmax D. Rectified linear units (ReLU) Answer: D New Question A Machine Learning Specialist trained a regression model, but the first iteration needs optimizing. The Specialist needs to understand whether the model is more frequently overestimating or underestimating the target. What option can the Specialist use to determine whether it is overestimating or underestimating the target value? A. Root Mean Square Error (RMSE) B. Residual plots C. Area under the curve D. Confusion matrix Answer: C New Question A company wants to classify user behavior as either fraudulent or normal. Based on internal research, a Machine Learning Specialist would like to build a binary classifier based on two features: age of account and transaction month. The class distribution for these features is illustrated in the figure provided. Based on this information, which model would have the HIGHEST recall with respect to the fraudulent class? A. Decision tree B. Linear support vector machine (SVM) C. Naive Bayesian classifier D. Single Perceptron with sigmoidal activation function Answer: C New Question A Machine Learning Specialist kicks off a hyperparameter tuning job for a tree-based ensemble model using Amazon SageMaker with Area Under the ROC Curve (AUC) as the objective metric. This workflow will eventually be deployed in a pipeline that retrains and tunes hyperparameters each night to model click-through on data that goes stale every 24 hours. With the goal of decreasing the amount of time it takes to train these models, and ultimately to decrease costs, the Specialist wants to reconfigure the input hyperparameter range(s). Which visualization will accomplish this? A. A histogram showing whether the most important input feature is Gaussian. B. A scatter plot with points colored by target variable that uses t-Distributed Stochastic Neighbor Embedding (t-SNE) to visualize the large number of input variables in an easier-to-read dimension. C. A scatter plot showing the performance of the objective metric over each training iteration. D. A scatter plot showing the correlation between maximum tree depth and the objective metric. Answer: B New Question A Machine Learning Specialist is creating a new natural language processing application that processes a dataset comprised of 1 million sentences. The aim is to then run Word2Vec to generate embeddings of the sentences and enable different types of predictions. Here is an example from the dataset: "The quck BROWN FOX jumps over the lazy dog." Which of the following are the operations the Specialist needs to perform to correctly sanitize and prepare the data in a repeatable manner? (Choose three.) A. Perform part-of-speech tagging and keep the action verb and the nouns only. B. Normalize all words by making the sentence lowercase. C. Remove stop words using an English stopword dictionary. D. Correct the typography on "quck" to "quick." E. One-hot encode all words in the sentence. F. Tokenize the sentence into words. Answer: ABD New Question A Data Scientist is evaluating different binary classification models. A false positive result is 5 times more expensive (from a business perspective) than a false negative result. The models should be evaluated based on the following criteria: 1) Must have a recall rate of at least 80% 2) Must have a false positive rate of 10% or less 3) Must minimize business costs After creating each binary classification model, the Data Scientist generates the corresponding confusion matrix. Which confusion matrix represents the model that satisfies the requirements? A. TN = 91, FP = 9 FN = 22, TP = 78 B. TN = 99, FP = 1 FN = 21, TP = 79 C. TN = 96, FP = 4 FN = 10, TP = 90 D. TN = 98, FP = 2 FN = 18, TP = 82 Answer: D Explanation: The following calculations are required: TP = True Positive FP = False Positive FN = False Negative TN = True Negative FN = False Negative Recall = TP / (TP + FN) False Positive Rate (FPR) = FP / (FP + TN) Cost = 5 * FP + FN Options C and D have a recall greater than 80% and an FPR less than 10%, but D is the most cost effective. New Question A Data Scientist uses logistic regression to build a fraud detection model. While the model accuracy is 99%, 90% of the fraud cases are not detected by the model. What action will definitively help the model detect more than 10% of fraud cases? A. Using undersampling to balance the dataset B. Decreasing the class probability threshold C. Using regularization to reduce overfitting D. Using oversampling to balance the dataset Answer: B Explanation: Decreasing the class probability threshold makes the model more sensitive and, therefore, marks more cases as the positive class, which is fraud in this case. This will increase the likelihood of fraud detection. However, it comes at the price of lowering precision. New Question Machine Learning Specialist is building a model to predict future employment rates based on a wide range of economic factors. While exploring the data, the Specialist notices that the magnitude of the input features vary greatly. The Specialist does not want variables with a larger magnitude to dominate the model. What should the Specialist do to prepare the data for model training? A. Apply quantile binning to group the data into categorical bins to keep any relationships in the data by replacing the magnitude with distribution. B. Apply the Cartesian product transformation to create new combinations of fields that are independent of the magnitude. C. Apply normalization to ensure each field will have a mean of 0 and a variance of 1 to remove any significant magnitude. D. Apply the orthogonal sparse bigram (OSB) transformation to apply a fixed-size sliding window to generate new features of a similar magnitude. Answer: C New Question A Machine Learning Specialist must build out a process to query a dataset on Amazon S3 using Amazon Athena. The dataset contains more than 800,000 records stored as plaintext CSV files. Each record contains 200 columns and is approximately 1.5 MB in size. Most queries will span 5 to 10 columns only. How should the Machine Learning Specialist transform the dataset to minimize query runtime? A. Convert the records to Apache Parquet format. B. Convert the records to JSON format. C. Convert the records to GZIP CSV format. D. Convert the records to XML format. Answer: A New Question A Data Engineer needs to build a model using a dataset containing customer credit card information How can the Data Engineer ensure the data remains encrypted and the credit card information is secure? A. Use a custom encryption algorithm to encrypt the data and store the data on an Amazon SageMaker instance in a VPC. Use the SageMaker DeepAR algorithm to randomize the credit card numbers. B. Use an IAM policy to encrypt the data on the Amazon S3 bucket and Amazon Kinesis to automatically discard credit card numbers and insert fake credit card numbers. C. Use an Amazon SageMaker launch configuration to encrypt the data once it is copied to the SageMaker instance in a VPC. Use the SageMaker principal component analysis (PCA) algorithm to reduce the length of the credit card numbers. D. Use AWS KMS to encrypt the data on Amazon S3 and Amazon SageMaker, and redact the credit card numbers from the customer data with AWS Glue. Answer: C New Question A Machine Learning Specialist is using an Amazon SageMaker notebook instance in a private subnet of a corporate VPC. The ML Specialist has important data stored on the Amazon SageMaker notebook instance's Amazon EBS volume, and needs to take a snapshot of that EBS volume. However, the ML Specialist cannot find the Amazon SageMaker notebook instance's EBS volume or Amazon EC2 instance within the VPC. Why is the ML Specialist not seeing the instance visible in the VPC? A. Amazon SageMaker notebook instances are based on the EC2 instances within the customer account, but they run outside of VPCs. B. Amazon SageMaker notebook instances are based on the Amazon ECS service within customer accounts. C. Amazon SageMaker notebook instances are based on EC2 instances running within AWS service accounts. D. Amazon SageMaker notebook instances are based on AWS ECS instances running within AWS service accounts. Answer: C New Question A Machine Learning Specialist is building a model that will perform time series forecasting using Amazon SageMaker. The Specialist has finished training the model and is now planning to perform load testing on the endpoint so they can configure Auto Scaling for the model variant. Which approach will allow the Specialist to review the latency, memory utilization, and CPU utilization during the load test? A. Review SageMaker logs that have been written to Amazon S3 by leveraging Amazon Athena and Amazon QuickSight to visualize logs as they are being produced. B. Generate an Amazon CloudWatch dashboard to create a single view for the latency, memory utilization, and CPU utilization metrics that are outputted by Amazon SageMaker. C. Build custom Amazon CloudWatch Logs and then leverage Amazon ES and Kibana to query and visualize the log data as it is generated by Amazon SageMaker. D. Send Amazon CloudWatch Logs that were generated by Amazon SageMaker to Amazon ES and use Kibana to query and visualize the log data Answer: B New Question A manufacturing company has structured and unstructured data stored in an Amazon S3 bucket. A Machine Learning Specialist wants to use SQL to run queries on this data. Which solution requires the LEAST effort to be able to query this data? A. Use AWS Data Pipeline to transform the data and Amazon RDS to run queries. B. Use AWS Glue to catalogue the data and Amazon Athena to run queries. C. Use AWS Batch to run ETL on the data and Amazon Aurora to run the queries. D. Use AWS Lambda to transform the data and Amazon Kinesis Data Analytics to run queries. Answer: B New Question A Machine Learning Specialist is developing a custom video recommendation model for an application. The dataset used to train this model is very large with millions of data points and is hosted in an Amazon S3 bucket. The Specialist wants to avoid loading all of this data onto an Amazon SageMaker notebook instance because it would take hours to move and will exceed the attached 5 GB Amazon EBS volume on the notebook instance. Which approach allows the Specialist to use all the data to train the model? A. Load a smaller subset of the data into the SageMaker notebook and train locally. Confirm that the training code is executing and the model parameters seem reasonable. Initiate a SageMaker training job using the full dataset from the S3 bucket using Pipe input mode. B. Launch an Amazon EC2 instance with an AWS Deep Learning AMI and attach the S3 bucket to the instance. Train on a small amount of the data to verify the training code and hyperparameters. Go back to Amazon SageMaker and train using the full dataset C. Use AWS Glue to train a model using a small subset of the data to confirm that the data will be compatible with Amazon SageMaker. Initiate a SageMaker training job using the full dataset from the S3 bucket using Pipe input mode. D. Load a smaller subset of the data into the SageMaker notebook and train locally. Confirm that the training code is executing and the model parameters seem reasonable. Launch an Amazon EC2 instance with an AWS Deep Learning AMI and attach the S3 bucket to train the full dataset. Answer: A New Question A company is setting up a system to manage all of the datasets it stores in Amazon S3. The company would like to automate running transformation jobs on the data and maintaining a catalog of the metadata concerning the datasets. The solution should require the least amount of setup and maintenance. Which solution will allow the company to achieve its goals? A. Create an Amazon EMR cluster with Apache Hive installed. Then, create a Hive metastore and a script to run transformation jobs on a schedule. B. Create an AWS Glue crawler to populate the AWS Glue Data Catalog. Then, author an AWS Glue ETL job, and set up a schedule for data transformation jobs. C. Create an Amazon EMR cluster with Apache Spark installed. Then, create an Apache Hive metastore and a script to run transformation jobs on a schedule. D. Create an AWS Data Pipeline that transforms the data. Then, create an Apache Hive metastore and a script to run transformation jobs on a schedule. Answer: B Explanation: AWS Glue is the correct answer because this option requires the least amount of setup and maintenance since it is serverless, and it does not require management of the infrastructure. A, C, and D are all solutions that can solve the problem, but require more steps for configuration, and require higher operational overhead to run and maintain. New Question A Data Scientist is working on optimizing a model during the training process by varying multiple parameters. The Data Scientist observes that, during multiple runs with identical parameters, the loss function converges to different, yet stable, values. What should the Data Scientist do to improve the training process? A. Increase the learning rate. Keep the batch size the same. B. Reduce the batch size. Decrease the learning rate. C. Keep the batch size the same. Decrease the learning rate. D. Do not change the learning rate. Increase the batch size. Answer: B Explanation: It is most likely that the loss function is very curvy and has multiple local minima where the training is getting stuck. Decreasing the batch size would help the Data Scientist stochastically get out of the local minima saddles. Decreasing the learning rate would prevent overshooting the global loss function minimum. New Question A Machine Learning Specialist is configuring Amazon SageMaker so multiple Data Scientists can access notebooks, train models, and deploy endpoints. To ensure the best operational performance, the Specialist needs to be able to track how often the Scientists are deploying models, GPU and CPU utilization on the deployed SageMaker endpoints, and all errors that are generated when an endpoint is invoked. Which services are integrated with Amazon SageMaker to track this information? (Choose two.) A. AWS CloudTrail B. AWS Health C. AWS Trusted Advisor D. Amazon CloudWatch E. AWS Config Answer: AD New Question A retail chain has been ingesting purchasing records from its network of 20,000 stores to Amazon S3 using Amazon Kinesis Data Firehose. To support training an improved machine learning model, training records will require new but simple transformations, and some attributes will be combined. The model needs to be retrained daily. Given the large number of stores and the legacy data ingestion, which change will require the LEAST amount of development effort? A. Require that the stores to switch to capturing their data locally on AWS Storage Gateway for loading into Amazon S3, then use AWS Glue to do the transformation. B. Deploy an Amazon EMR cluster running Apache Spark with the transformation logic, and have the cluster run each day on the accumulating records in Amazon S3, outputting new/transformed records to Amazon S3. C. Spin up a fleet of Amazon EC2 instances with the transformation logic, have them transform the data records accumulating on Amazon S3, and output the transformed records to Amazon S3. D. Insert an Amazon Kinesis Data Analytics stream downstream of the Kinesis Data Firehose stream that transforms raw record attributes into simple transformed values using SQL. 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