Waived!

# ATA MINING Homework Clustering andMonte Carlo SimulationYou should return a Python notebook with

(5 customer reviews)

Original price was: \$10.00.Current price is: \$5.00.

Full support will be provided with necessary files installation.

Get impeccable customized solution within 24 hours, hassle-free.

Solved By Verified
Study Co-Pilot
Instant

## Description

ATA MINING Homework: Clustering andMonte Carlo SimulationYou should return a Python notebook with your code and the answers to the questions. You are provided with a dataset that includes information about various movies such as budget, IMBD score, duration etc.: A- . Provide a good clustering for the data and a description of them (i.e., what type of movies do they include) Hint: Examine up to 20 clusters.b. As you will observe, the various features of the data are in different scales. In these cases, normalizing the data helps into obtaining better models – either supervised or unsupervised. Use the sklearn.preprocessing.normalize function to normalize the data and perform the clustering again. What do you observe? c. Visualize the data on a 2D scatter plot, where each point corresponds to a movie and movies that belong to the same cluster have the same color. What do you observe with regards to their visual separability? budgetgrossruntimescorevotes800000052287414898.12991746000000701363691037.8264740150000001.8E+081106.923690918500000851602481378.4540152900000018564613906.93663660000001.39E+081208.131758525000000127299171017.4102879600000085512281207.8146768900000040471663966.8605651500000040456565967.512969888000001.75E+08976.5794651600000059000001167.2104860600000082000001006.8122282500000011100000997.31016781500000086209291207.2540001700000067348441175.931798100000007433663985.4248812500000038747385946.95332727000003500000935.91163535000000162957741104.636020200000013167232826255171100000091258000966.62312047000008025872895.62125315000000427240171306.832954250000001.1E+081197.366366040697761986.647068071534871307.8869910241598721175.3113042500000079817937945.94299719000004600000997.11286225000000392467341046.4574062500000049042224875.754851020038221207.41456224500000172180231257.547497138000005229398211976249501.15E+081135.958370071774311146.5462360000005844868977.3361911000000037499651916.341278300000019472057865.92831025000000143027791176.623076047483002806.941004400000028265231127.1250321000000047112201053.8440145000001261000866.71663618000000413828411036.3285291900000040996665915.72066911000005450815824.375690385007261076.593440262855441065.910239111000609939837253671800000096977391075.6114846400000400840411078569881400000038600000747.2365398500000162094591065.52485160000005849647847.33360902015882917.240395000000591366886.8160771200000048846631005.5587805839031997.1114156000000286075241147.63660403006531498.116571650000023470001117116070154483841106.11041204662137855.612803014481606935.31002220000000253142891086.17570150000001953732985.3534012000000177689001255.61581908988731915.554190387023101136.2123070278200001045.26440013431806936.41158106797218985.8458518000000366116101126.2996502514705510364943043579163835.2354431750007137502846.65257071624879936.922554870000048659121096.32297051866461106.438660318530801197.2125381200000015945534885.69040110000014360001077.83945610000000206037151096.714502013245219907.19178083629691146.9131861800000039000001176.14666500000012947763896.211458250000001579260944.833970176853071026.6100220255878041055.8157034000000016418251216.1659605274807.8790010000000214582291046.25584020695211078959066375651005.440451200000077909311045.9552320000007369373985.7474414000000621342251036.11356985000002776461367.25364076349091055.637200595845686621250916172875.758431800000013051141155.736070123039041065.7556408033397825.655490320256835.7462003751699994.47491057941841047.4107470323245571185.953458000000118343021045475204834601176264933000004941117935.9390903151936.740720214831167.34922046361691036.612641500000012308521964.9504940000000498515911165.9837401476356966.69689013418091896.327051300000084754661005.64573024440761014.5680049409391208.12091402510433945.2171703940542113817849170000002315683973.143391600000038000001115.722870604849845.9102320000000229055001056.4307902278264915.5300604601256964.5142202147228963.32003600000099476311005.93561025451429073885010090429984.925490278623955.9183409302111085.62659032726001337.44028400000046796501045.9180802995527965.43400112132885.82243048457241024128405099316935.4101604781448975.6142618000000119579431086.92720037455987.8461203136701975.5327017204501005.9208001131399905.421570441863967.6184006029824904.51164078068882.989502037811557.326940277405865.73230239073855.315401409801025.29782500000040072501275.5134002750741934.69731700000027932141015.51358012540401015.868402750001005.49070142050211065.723000681337914.712650537681907.8233008540346765.317601400000018034150976.31288019437511005.363234013763388020974.31509100000006947787834.47920544472907.21623026693661024.151508736107769905633581075.56520444746886.2639040798951026.11032014926895.37950750000966.6162507250001057.82991019027061017.3662204743287885.7553015000001006.21672200000013011211115.944804163931056.682101777378936.56040925952847202205838001006.227501814101005.1310

## 5 reviews for ATA MINING Homework Clustering andMonte Carlo SimulationYou should return a Python notebook with

1. Lynn Prytula

Work was finished long before due and tutor was considerate and engaging. Perfect!

2. Megan Mowles

great and amazing work, highly recommend. God bless you in all your days 🙂

3. John Chaple

Awesome work as usual!!

Excellent job, my friend. Thank You!!

5. Kirsten Gorby

I am pleased for the assistance to get a answer to my questions. The service is prompt and provides good value to me.

Only logged in customers who have purchased this product may leave a review.