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MachineLearning Assignment 1 Solved

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  • Problem 1

Import the numpy package under the name np

Create a vector or 1D array with 10 zeros and print it

Find the memory size of this array

[ ]: array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])

[ ]: print(“The Size of the array is”, arr.itemsize*arr.size, “Bytes”)

The Size of the array is 80 Bytes

  • Problem 2:

Create another vector or 1D array with values ranging from 10 to 20

Reverse the created vector (first element becomes last) — Is there any NumPy method that you can use?

[ ]: array([10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20])

[ ]: array([20, 19, 18, 17, 16, 15, 14, 13, 12, 11, 10])

  • Problem 3:

Create a 3×4 array with random values (standard normal distribution) and find the minimum and maximum values

[ ]: array([[8672, 9272, 6342],

[3784, 5232, 7887],

[5001, 4270, 3926],

[6843, 5154, 7836]])

[ ]: arr3.max()

[ ]: 9272

[ ]: arr3.min()

[ ]: 3784

  • Problem 4:

Given the following 1D array, negate all elements which are between 3 and 8, in place. (include both 3 and 8 in conditional statements)

[ ]: Z

[ ]: array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10])

[ ]: array([ 0, 1, 2, -3, -4, -5, -6, -7, -8, 9, 10])

Given the 1D array Z, find the closest value to the given scalar v?

[ ]: Z

[ ]: array([ 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21,

22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38,

39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55,

56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71, 72,

73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89,

90, 91, 92, 93, 94, 95, 96, 97, 98, 99])

Closet Value is %d 33

Subtract the mean of each row of the following matrix

␣

,→—————————————————————————

NameError                                                                    Traceback (most recent call␣

,→last)

<ipython-input-1-3b30b7c6267b> in <module>() —-> 1 np.random.seed(2)

  • X = np.random.rand(3, 4)
  • print(X)

NameError: name ‘np’ is not defined

[ ]: array([[0.3617265 , 0.3617265 , 0.3617265 , 0.3617265 ],

[0.39365556, 0.39365556, 0.39365556, 0.39365556],

[0.42918947, 0.42918947, 0.42918947, 0.42918947]])

[[ 0.0742684 -0.33580027 0.18793598 0.07359589] [ 0.02671225 -0.06332073 -0.18900692 0.22561541]

[-0.1295348 -0.16236219 0.19194436 0.09995263]]

Timing comparison for multiplication of 4 arrays. Find the fastest way to compute the multiplication ABCD. Make sure you report the elapsed time. (hint: you can find relevant information at https://youtu.be/SeBRHg9ZrSs) Complete the following:

5    Problem 5

Import and print the file ’parks.csv’ (Park Code should be the index column)

<IPython.core.display.HTML object>

[ ]:                                                                                               Park Name         … Longitude

Park Code                                                                                                    …

ACAD                                                      Acadia National Park           … -68.21
ARCH                                                      Arches National Park           … -109.57
BADL Badlands National Park … -102.50
BIBE Big Bend National Park … -103.25
BISC Biscayne National Park … -80.08
BLCA               Black Canyon of the Gunnison National Park              … -107.72
BRCA                                           Bryce Canyon National Park           … -112.18
CANY                                             Canyonlands National Park           … -109.93
CARE                                            Capitol Reef National Park            … -111.17
CAVE                                    Carlsbad Caverns National Park            … -104.44
CHIS                                       Channel Islands National Park             … -119.42
CONG Congaree National Park … -80.78
CRLA                                             Crater Lake National Park            … -122.10
CUVA                                      Cuyahoga Valley National Park            … -81.55
DENA Denali National Park and Preserve … -150.50
DEVA Death Valley National Park … -116.82
DRTO Dry Tortugas National Park … -82.87
EVER Everglades National Park … -80.93
GAAR Gates Of The Arctic National Park and Preserve … -153.30
GLAC Glacier National Park … -114.00
GLBA Glacier Bay National Park and Preserve … -137.00
GRBA Great Basin National Park … -114.30
GRCA Grand Canyon National Park … -112.14
GRSA Great Sand Dunes National Park and Preserve … -105.51
GRSM Great Smoky Mountains National Park … -83.53
GRTE Grand Teton National Park … -110.80
GUMO Guadalupe Mountains National Park … -104.87
HALE Haleakala National Park … -156.17
HAVO Hawaii Volcanoes National Park … -155.20
HOSP Hot Springs National Park … -93.05
ISRO Isle Royale National Park … -88.55
JOTR Joshua Tree National Park … -115.90
KATM Katmai National Park and Preserve … -155.00
KEFJ Kenai Fjords National Park … -149.65
KOVA Kobuk Valley National Park … -159.28
LACL Lake Clark National Park and Preserve … -153.42
LAVO Lassen Volcanic National Park … -121.51
MACA Mammoth Cave National Park … -86.10
MEVE Mesa Verde National Park … -108.49
MORA Mount Rainier National Park … -121.75
NOCA North Cascades National Park … -121.20
OLYM Olympic National Park … -123.50
PEFO Petrified Forest National Park … -109.78
PINN Pinnacles National Park … -121.16
REDW Redwood National Park … -124.00
ROMO Rocky Mountain National Park … -105.58
SAGU Saguaro National Park … -110.50
SEKI Sequoia and Kings Canyon National Parks … -118.68
SHEN Shenandoah National Park … -78.35
THRO Theodore Roosevelt National Park … -103.45
VOYA Voyageurs National Park … -92.88
WICA Wind Cave National Park … -103.48
WRST Wrangell – St Elias National Park and Preserve … -142.00
YELL Yellowstone National Park … -110.50
YOSE Yosemite National Park … -119.50
ZION                                                         Zion National Park           … -113.05

[56 rows x 5 columns]

Print all column names

[ ]: list(parks.columns) [‘Park Name ‘, ‘State ‘, ‘Acres ‘, ‘Latitude ‘, ‘Longitude ‘] Make sure tha all letters are lower case and replace space with _

[ ]: parks = parks.astype(str).apply(lambda x: x.str.lower())

[ ]: parks = parks.astype(str).apply(lambda x: x.str.rstrip())

[ ]: parks = parks.astype(str).apply(lambda x: x.str.replace(‘ ‘,’_’))

[ ]: parks[“State “] = parks[“State “].apply(lambda state: state.replace(‘_’,”)) Which state has the smallest national park?

[ ]: 5550

[ ]:                                                       Park Name State               Acres Latitude Longitude

Park Code

HOSP                 hot_springs_national_park              ar        5550          34.51           -93.05

State is Arkansas

Produce a histogram plot that shows the distribution of ’acres’.

[ ]:

  • Assign1-mcobxc.zip

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