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Love It Or Hate It: Live Sporting Events?
Welcome to the Funny Community game, Love It Or Hate It! This game is really similar to Monday's 'No Good or So Good' food game - except this one deals a lot more with non-food things. Every week, I highlight a different thing that a lot of people either really love or really hate and see how our community feels overall! Last week, I asked you how you felt about SELFIE STICKS. It was an EXTREMELY tight vote, but out of the 60 who gave your opinion, 33 of you said that they're actually kind of useful! Soooo... SELFIE STICKS WIN!!!! This week, I want to know: How do you feel about attending live sports games? Spectator sports have been around since the days of Ancient Greece, but the ones we know and love today came into being in the mid 19th century! The number of Americans that attend at least one live sporting event annually is easily in the tens of millions. However, the amount of them that find said sporting event COMPLETELY BORING is still widely unknown. How do YOU feel about spectator sports? Are they tons of fun or brutally boring? Debate, debate, debate! @Inaritricx @Taijiotter @wonyeop316 @AimeeH @XergaB20 @JustinaNguyen @Danse @RainaC3 @bnrenchilada @destiny1419 @arnelli @Luci546 @InPlainSight @Ash2424701 @GingerMJones @zwdodds @LenaBlackRose @misssukyi @TerraToyaSi @kneelb4zod @BrookeStam @RachelParker @JaxomB @ultraninja10 @reyestiny93 @MattK95 @MajahnNelson @petname83 @BluBear07 @melifluosmelodi @ZoilaObregon @GossamoKewen95 @TracyLynnn @TiffanyWallace @VixenViVi @DenieceSuit @ButterflyBlu @CelinaGonzalez @MaighdlinS @maddiemoozer @VeronicaArtino @iixel @TomHawthorne @DominiqueThomas @ElizabethT @RiggaFoster @AluSparklez @kvnguyen @chris98vamg @WiviDemol @animechild51 @2Distracted @cthulu @jazziejazz @JessicaChaney @shantalcamara @J1mbleJ4mz @Beeplzzz @carmaa10 @MayraYanez @Kamiamon @HeatherWright @MischiefK1ng @SeoInHan @ShonA @KennyMcCormick @MooshieBay @IMNII @Ikpoper @humairaa @merryjayne13 @zoemvillarreal @lilleonz @ChristinaOMalle @AllieGrabowski @baileykayleen @KarleyFrance @Ticasensei @EasternShell @musicundefined9 @peahyr @TerrecaRiley @MoisEsGaray @atmi @AlidaGarman @sanRico @orenshani7 @jannatd93 @ReadAnimateSwim @Astrohelix @dimplequeen @ChildofSparda13 @grapetoes2000 @sarahpjane @LittleHorn @justinasarmento @deilig @GalaxyTacoCat @amobigbang @LAVONYORK @Jason41 @kpopdeluxegirl @BlackDragon88 @Bobs @paularasnick @Animaniafreak @YumiMiyazaki @Patmanmeow @MarvelTrashcan @kawaiiporpoise @Xiuyeolhyun @MaggieHolm @xDaisyDaysx
Dự đoán XSMN thứ 2 6/4/2020 – Soi cầu dự đoán KQXSMN
Dự đoán XSMN thứ 2 6/4/2020 – dự đoán soi cầu XSMN ngày 6 tháng 4 tại Tinycat99, với hệ thống thống kê đầy đủ và chính xác sẽ cho các bạn những con số may mắn nhất. Phân tích & Dự Đoán XSMN thứ 2 6/4/2020 Thống kê lô gan MN lâu chưa về Soi cầu dự đoán XSMN chính xác nhất Việt Nam https://tinycat99.click/du-doan-xsmn-thu-2-6-4-2020-soi-cau-du-doan-kqxsmn/ Thống kê lô gan miền nam – kết quả miền Nam thứ 2 6/4/2020 Thống kê Lô gan miền Nam (thống kê lô khan mn, số rắn miền Nam) giúp người chơi nắm được chính xác những con số lô tô gan lâu ra nhất, những cặp lô lâu chưa về trong thời gian gần đây, qua đó có thể chọn cho mình những cặp số có khả năng về cao nhất và chính xác nhất. Theo dõi những thống kê lô gan mn lâu chưa ra nhất của chúng tôi, ngoài việc có thể dễ dàng biết được những cặp số lâu ra nhất là những cặp số nào, các bạn còn có thể thống kê được những cặp số đẹp nhất, những cặp số ra nhiều nhất là những cặp số gì, thống kê lô gan xsmn của các đài mở thưởng hôm nay. Thống kê dự đoán XSMN thứ 2 6/4/2020 hôm nay sẽ đưa ra cho người chơi thông tin của các cặp số đầu đuôi lô tô miền nam về trong thời gian gần đây hỗ trợ bạn trong việc lựa chọn cặp số may mắn ngày 4/4/2020, cụ thể: Tinycat99 – Dự đoán XSMN thứ 2 6/4/2020 chuẩn xác Sự khác biệt của bảng dự đoán XSMN 6/4/2020 tại Tinycat99 so với các trang xổ số khác là các con số được đưa ra dựa vào các tính toán truyền thống cùng với hệ thống máy học kết hợp với hệ thống siêu máy tính phân tích từ dữ liệu nhiều năm cùng với các chuyên gia đầy kinh nghiệm của Tinycat99 sẽ cho tỉ lệ trúng giải cao và chính xác. Tuy nhiên, mọi con số đều mang tính chất dự đoán và may mắn phụ thuộc vào việc chọn lựa của bạn. Tham khảo thêm về Soi cầu dự đoán XSMB, dự đoán XSMT tại hệ thống mạng XH của Tiny cat99: https://sites.google.com/view/soicautinycat99/
This Means So Much: Chile's Copa America win goes beyond sport
I am not Chilean, and I don't pretend to be. But that doesn't mean I can't hold allegiance to Chile. I spent six months there last year - a long time in the life of a 21-year-old - and, thanks to the people that I met, developed a legitimate sense of belonging in Santiago. I lived with Chileans. I went to school with Chileans. I went drinking, and hiking, and rock climbing, and bike riding, and shopping with Chileans. I am not Chilean, but, for those six months, that was easy to forget. When you send - no, throw - yourself into a foreign place for an extended period of time and provide yourself with essentially no outlet to the life that you've known for twenty years, you learn things. When your daily interactions are with people who have experiences and histories so dramatically different than your own, you learn about these experiences and histories, and you begin to feel, in small ways, that they belong to you, too. When you watch the national soccer team fall to big-bad Brazil, twice hitting the post in uniquely Chilean, heartbreaking fashion, you come to realize that the sort of national bad luck that Chileans refer to may hold some tragic water, and you come to realize how much this sport means to people. When you cover your nose and mouth from the July smog, when you grow frustrated with bureaucratic inconsistencies, when you unsuspectingly ride your bike through the Molotov-cocktail-stained black streets of a protest and get nailed with tear gas, you begin to understand what it means to be a Santiaguino. When you remember all this and look out your window in the morning and gasp at the breathtaking Andes looming, you know. At that point, it doesn't matter if you've lived there for six months or six lifetimes. When you have one the most honest conversations of your life with the woman who did more for you in your six months than you can attempt to relate in words or images - not to mention giving you a bed, food, and invaluable access and welcoming into a family - you listen to it in a way you didn't know you were capable; you listen, and you remember. When Ximena tells you why she will never return to the Estadio Nacional, the sports complex in the middle of Santiago that contains the soccer pitch where Chile beat Argentina on penalties this weekend to win Copa América - Chile's first ever major international championship - you remember it. And you share the pain and sorrow, as well as you can manage. Ximena will never return to Estadio Nacional because she was there, once, in 1973. She was fortunate to be on the outside, perilously looking in; had she been on the other side of its doors, she may not have reemerged. On September 4, 1970, socialist candidate Salvador Allende was democratically elected as president of Chile. On September 11, 1973, Allende died under mysterious circumstances after delivering his very last speech, in the face of a brutal coup d'etat by General Augusto Pinochet and a junta of right-wing economists and military leaders. Pinochet would hold the position of dictator until 1990. In those seventeen years, an estimated 3,000 Chileans were executed or declared 'disappeared', and another 200,000 were exiled. Those tortured, humiliated and murdered were everything from left-wing politicians to artists to intellectuals to musicians to young students. These izquierdistas were captured from their families, often without notice and brought to detention centers all along the long, thin coastal nation. Some of these centers still stand today, including the harrowing Villa Grimaldi (pictured above), which lies in the outskirts of a wealthy neighborhood of Santiago. It's a museum, now, and a visit leaves a lump in your throat twice the size of an apple. The lump stays with you well after you exit its gate, occupying a place in your heart that will never be overtaken. The thick, original padlock from its days as a torture center still remains on the door, symbolically locked shut forever. A visit to the national cemetery, also in Santiago, has a similarly chilling effect. Allende's tombstone and the plaque that sits next to it, chronicling part of his final speech, stand out, but not more so than the thousands of graves that do not exist, and never will. These desaparecidos are commemorated on a much-too-large wall at the cemetery's exit. The wall, too, leaves a lump inside you. Some words from Allende's final speech: "Trabajadores de mi Patria, tengo fe en Chile y su destino. Superarán otros hombres de este momento gris y amargo en el que la traición pretende imponerse. Sigan ustedes sabiendo que, mucho más temprano que tarde, de nuevo se abrirán las grandes alamedas por donde pase el hombre libre, para construir una sociedad mejor. ¡Viva Chile! ¡Viva el pueblo! ¡Vivan los trabajadores!" "Workers of my country, I have faith in Chile and its destiny. Men will overcome this dark and bitter moment when treason seeks to prevail. Go forward knowing that, sooner rather than later, the great avenues will open again where free men will walk to build a better society. Long live Chile! Long live the people! Long live the workers!" Estadio Nacional was, unthinkably, used by Pinochet and the persecutors of the dictatorship's terror as a detention center. A prison. A torture den. And on Saturday, the Chilean national team won a match there that comes as close as anything ever has at appeasing the tragedies of the 1970s. Any Chilean you speak to who was alive in the '70s will have a story of their experience. Many were exiled, and later returned. Many went far, far away, and will never come back. Some have relatives that were abducted. Others no longer speak to their families - differences in opinion regarding the coup are too extreme to be ameliorated, even forty years later. Some, like Ximena, ran away from home as a teenager in '73, appalled at her mother's support for Pinochet's coup and madly in love with a man with similar troubles. While some are capable of forgiveness - Ximena and her mother see one another often, now - others cannot fathom the meaning of the word. The stains are too deep, for many. Estadio Nacional stands today as it did when Pinochet exploited it as a symbol of his power. Off the side of a busy avenue, the unknown behind its walls and fences struck unspeakable fear into Chileans, desperate to know what had come of their disappeared loved ones. It was as visible as anything, yet there are very few accounts explaining what actually went on, or who was taken, or whether or not they ever left. There are few records; there is extraordinary memory. Each time the stadium packs full, a small section is left empty. "Un pueblo sin memoria es un pueblo sin futuro," a sign reads. "A people without memory is a people without future." But there's no concern here that Chileans will forget. Remembering is part -- the part, perhaps -- of the Chilean experience. And this focus on memory is part of what made the victory in the Copa América so special. Chileans remember the match against Brazil last June. They remember that this group of Chilean players is labeled the "Golden Generation" - it's the best team they've ever had, and it represents the best chance they've ever had at winning a major title. They remember that the tournament is being played at home in Chile. They remember what went on in the arena that was to host the final. But the cynicism that is so natural to most Chileans would have told them that something would've gone wrong in the tournament. It seemed it might when start Arturo Vidal was involved in a drunk driving accident in the group stages, but the team rallied behind his continued presence in the team. Chances seemed slim throughout a brutal, physical affair with Uruguay in the quarterfinals, a match that was marred with controversy, but Chile fought harder and earned their win. When spirited Peru, playing down a man, equalized in the second half, there were fears that it would all come crashing down at the hands of their biggest rival, but Edu Vargas responded with a goal for the ages. When Argentina clobbered Paraguay to set up a match with Chile in the final, victory seemed improbable. Up and down the team sheets, Argentina are better than Chile. When they battled for 120 minutes and readied themselves for penalties, the cynicism perked up again, and the nation remembered the penalty shootout that crushed their dreams against Brazil in the World Cup. The win means so much to a nation plagued by bad luck - in the forms ranging from Pinochet's rule (though luck does no justice for what occurred), to missed penalty kicks, to crippling, unpredictable earthquakes, volcanic eruptions and, perhaps most famously, the entrapment of 33 miners for more than two months. The win goes beyond the score, the way the game was played, and the sport as a whole. This is a unifying event for Chileans all around the world - including those who will never return following their exile, and those of us who borrowed the nation, its culture and its amazing people for only a short time. I maintain my U.S. passport; that won't change. I may speak Spanish with a surprising Chilean accent, but that does not make me Chilean. I may have memories like the ones I've written about above, but those don't serve to change my nationality, either. I may have shared the agonizing defeat to Brazil in 2014, but that does not mean I share the memory of two decades of unjust political and social oppression. I do not have memories of that. But I do have understanding; I do have empathy; I do relate; I do recognize; I do smile; I do remember. I do reach out to Chilean friends and near-family, and they do appreciate it, because they know, better than I do, what it means. And when it means that much, maybe knowing that there's a kid sitting in New York thinking of them helps it mean even just a drop more.
Andy Murray headlines Great Britain Davis Cup finals team
Andy Murray surprised the tennis world on Sunday by winning the European Open in Antwerp. The Scotsman had been out of the limelight of tennis over the last year following hip surgery. Murray had struggled to regain form and fitness following the procedure and Sunday’s win at the European Open was his first victory in two years. Tennis fans can enjoy Murray’s return to action. The tennis star is expected to return to the courts at the Davis Cup finals in November. The tennis tournament in Madrid will feature Murray alongside captain Leon Smith, Dan Evans, Jamie Murray, and Neal Skupski. The tournament will see Murray compete in the Davis Cup for the first time since 2016. Great Britain last won the Davis Cup in 2015. Great Britain will start the Davis Cup finals against The Netherlands on 20 November and Kazakhstan on 21 November. Despite Murray’s return to winning tennis, injuries could see the tennis star struggle to win further events. Murray has been praised by tennis players and pundits following his win at the European Open. However, the positivity hasn’t carried over to everyone. Swiss surgeon Dr Hannes Rudiger has warned Murray that he faces “catastrophic consequences” if he continues to play tennis. Murray is just 32-years old and still has – barring injury – more years left to play. At least he does theoretically. Great Britain may have Murray in their Davis Cup finals team but they are 10th in odds according to major bookmakers. Spain, France, Croatia, and the United States lead the way in Davis Cup finals odds for the tournament in November. While Murray may not be able to lead Great Britain to success in Madrid, the tennis star is nearing his best once more. Perhaps next season he could be back in his best form. How good was Murray at the European Open? According to stats kept at the tournament in Antwerp, Murry was hitting the ball seven miles per hour faster on his backhand side. Pundits also raved about Murray’s serve and ball toss during the tournament. Both his backhand and ball toss were credited as reasons for his win over Stan Wawrinka. Murray isn’t the only major tennis star set to play at the Davis Cup finals. Novak Djokovic, Rafa Nadal, and Daniil Medvedev will all be competing for their respective countries. This year’s Davis Cup will be a history-making event played at Madrid’s La Caja Magica. Eighteen nations in all will compete for the finals trophy. According to leading sportsbooks, the longest shots to win the finals are the Netherlands, Kazakhstan, and Colombia. Each nation is at 100/1 odds to win the event. Both the Netherlands and Kazakhstan will open the tournament against Great Britain. The Davis cup finals will have a round-robin tournament format with teams playing in groups. The winner of each group along with the following two best teams will advance to the knockout stages. Ties will see two singles matches and one doubles rubber match. They will also feature the best of three tie-break sets.
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New Question An engineer is seeking the most optimal on demand CPU performance while configuring the BIOS settings of a UCS C-series rack mount server. What setting will accomplish this goal? A. C6 Retention B. C6 non-Retention C. C2 state D. C0/C1 state Answer: A New Question An engineer is duplicating an existing Cisco UCS setup at a new site. What are two characteristics of a logical configuration backup of a Cisco UCS Manager database? (Choose two.) A. contains the configured organizations and locales B. contains the VLAN and VSAN configurations C. contains the AAA and RBAC configurations D. contains all of the configurations E. contains a file with an extension tgz that stores all of the configurations Answer: BC New Question A Cisco MDS 9000 Series Storage Switch has reloaded unexpectedly. Where does the engineer look for the latest core dump file? A. /mnt/recovery B. /mnt/core C. /mnt/logs D. /mnt/pss Answer: D New Question An engineer must implement a Cisco UCS system at a customer site. One of the requirements is to implement SAN boot. The storage system maps the source WWPN to a unique LUN. Which method does Cisco recommend to configure the SAN boot? A. Define the vHBAs as bootable and leave the boot target definition empty. B. Create a SAN boot policy in which every initiator is mapped to a different target LUN. C. Define the vHBAs as bootable and leave the default values on the boot target definition. D. Create a SAN boot policy in which every initiator is mapped to the same target LUN. Answer: D New Question In an FCoE environment, for which two sets of data must an interface that implements the PAUSE mechanism always provision sufficient ingress buffer? (Choose two.) A. frames that were sent with high credit B. frames that were sent on the link but not yet received C. frames that were processed and transmitted by the transmitter after the PAUSE frame left the sender D. frames that were processed and transmitted by the transmitter before the PAUSE frame left the sender E. frames that were sent on the link and received Answer: BD New Question What are two types of FC/FCoE oversubscription ratios? (Choose two.) A. switch processing power to end-node processing power B. port bandwidth to uplink bandwidth C. server storage to end-node count D. edge ISL bandwidth to core ISL bandwidth E. host bandwidth to storage bandwidth Answer: DE New Question Refer to the exhibit. An engineer is implementing zoning on two Cisco MDS switches. After the implementation is finished, E Ports that connect the two Cisco MDS switches become isolated. What is wrong with the implementation? A. Zones are local to the MDS switch and name service must be used to activate the connection between E Ports. B. Different zone set names must be configured on both MDS switches. C. Zones must have the same name on both MDS switches for the E Ports to function. D. E Ports on both MDS switches must be configured as F Ports for the zoning to function. Answer: A New Question An engineer is implementing NPV mode on a Cisco MDS 9000 Series Switch. Which action must be taken? A. NPIV must be enabled on the upstream switch. B. The FCNS database must be disabled in the fabric. C. A port channel must be configured to the upstream switch. D. All switches in the fabric must be Cisco MDS switches. Answer: A New Question Which two statements about modifying Cisco UCS user accounts are true? (Choose two.) A. Disabling a user account maintains all of the data in the Cisco UCS Fabric Interconnect. B. The admin account can be used to log on by using SSH only. C. The password of the user account must contain a minimum of 10 characters. D. Local user accounts override the same account on a remote authentication server, such as TACACS, RADIUS, or LDAP. E. The password of the user account expires in 30 days. Answer: AD New Question An engineer must ensure fabric redundancy when implementing NPV mode on a Cisco MDS 9000 Series Switch. Which action enables fabric redundancy? A. Use TE ports to connect to upstream switches. B. Add a port channel to upstream switches. C. Configure the NPV devices to use an external FLOGI database. D. Connect the NPV devices to multiple upstream switches. Answer: B New Question An engineer is converting a Cisco MDS switch to support NPIV mode. What should be considered when implementing the solution? A. It requires mapping of external interface traffic. B. It must be enabled on VSAN 1 only. C. It must be enabled globally on all VSANs. D. It requires the FLOGI database to be disabled. Answer: C New Question Refer to the exhibit. What is the result of implementing this configuration? A. The Fibre Channel interface is configured for SPAN. B. The Fibre Channel interface is configured for source distribution. C. The Fibre Channel interlace is configured for FSPF. D. The Fibre Channel interface is configured for synchronization distribution. Answer: A Resources From: 1.2020 Latest Braindump2go 350-601 Exam Dumps (PDF & VCE) Free Share: https://www.braindump2go.com/350-601.html 2.2020 Latest Braindump2go 350-601 PDF and 350-601 VCE Dumps Free Share: https://drive.google.com/drive/folders/1M-Px6bHjOJgp4aPsLoYq-hgm90ZKxV_i?usp=sharing 3.2020 Latest 350-601 Exam Questions from: https://od.lk/fl/NDZfMTI1MTQ4N18 Free Resources from Braindump2go,We Devoted to Helping You 100% Pass All Exams!
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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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