52- Logistic regression and image classification case study in Python-(Day-25)

[@Codanics]

Like the video and comment below to let KZbin know that you are learning Machine learning with Codanics.

[@syedabdulwahabshah3280]

i have followed your video and my accuracy score is o.56,0.58,0.59 why ? also my predicted answer come in float number ?

[@asadtariq6080]

For **Assignment Hint** Indentation errors are pretty common in Python. Understand the logic what we actually want to save and what we actually are saving. Debugging is the way to troubleshoot your problem, you can simply print out each data in the loop and check whats the mistake(desi Debugging :D ).

[@HsnHny]

0:01 Start Watching Logistic Regression and Image Classification Case Study.

[@aajizattari]

27:50, the statement "index+=1" on line 10 of the cell, is currently inside if statement. It should be indented back one level so that the code functions properly1

[@asadtariq6080]

12:35 Import warnings filter to remove unnecessary warnings. ``` import warnings warnings.filterwarnings('ignore') ```

[@muhammadammarmohsin107]

0:01 Started #DataScience #artificailIntelligence #deeplearning #machinelearning #python #python_ka_chilla #baba_aammar #machine_learning #simple_linear_regression #multiple_linear_regression

[@saman__fatima]

plt.figure(figsize=(20,4)) for index,(image,label) in enumerate(zip(digits.data[0:10],digits.target[0:10])): plt.subplot(1,11 , index+1) plt.imshow(np.reshape(image, (8,8)),cmap=plt.cm.gray) plt.title('training: %d ' %label, fontsize = 20)

[@ramizch1739]

@samanfatima how to get these long codes

[@zainabbhatti8330]

17:17(from sklearn import metrics) and then metrics.confusion_matrix()

[@SaleemKhan-vv3ks]

Great job Murshid. #LearningML_with_codanics

[@farmanullah388]

16:45 Import the library and also define the prediction variable

[@AR-Edzone]

17:13 From sklearn import metrics And then move further

[@YasirMehmood-ni1zh]

Time Pause #17:23 Import Library from sklearn import metrics

[@faizanarshad7927]

Yes. Started!

[@ehtishamahmad2032]

16:46 importing metrices from sklearn library

[@MuhammadArslan-dz9fi]

#17:13 From sklearn import metrics

[@mehwishhanif4547]

Started watching

[@FAIFACTS]

Started watching Sir

[@quratulainhabib8748]

started watching logistic regression and image classification case study in Python.

[@danishnawaz1625]

26:00 Due to wrong indentation predicted and actual values are same

[@goharrahman5611]

Started 17:00 from sklearn import matrix

[@ahmedullah8799]

17:10 first import the matrice from sklearn and then go through

[@harisahmed6901]

Video completed and implemented sir :)

[@amnafarooq5871]

17:17 from sklearn import metrix import confusion matrix

[@Fayez-tk7ph]

Started!

[@mehramali4652]

Starting watching

[@workplace9672]

16:44 from sklearn import metrics

[@azeemjaved9963]

@17:14 from sklearn import metrics

[@mmateenalihashmi7440]

started watching....

[@abro87]

watched completely

[@NasirJumani]

0:00 Started watching

[@asadtariq6080]

18:10 Syntax Error because of Spelling of 'prediction'

[@nabeelarajput7316]

Started .

[@muhammadabubakar8930]

0:00 Started

[@naseerkhan-lu8kn]

16:47 matrices spelling error, metrics, Confusion matrix import is miss from sklearn

[@islamhussain8026]

Started 🙂

[@fahadnajeeb6132]

00:01 started

[@sammadullah8254]

started..

[@sana_131]

#ML_with_codanics❣️

[@shahidiqbal0506]

Logistic regression and image classification is clear

[@fahadnajeeb6132]

16:35 library not imported confusion matrices

[@hassanorakzai8981]

@0:01 Start watching

[@muhammadtayyabfarooq7283]

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[@faheemk1111]

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[@farmanullah388]

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[@ikrambashir8604]

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[@ishanbanjara734]

ASSIGNMENT _________________________________ #Get missclassified Labels index=0 MCI=[] for label, predict in zip(y_test,predictions): if predict!=label: MCI.append(index) index+=1 plt.figure(figsize=(20,4)) for index,misclass in enumerate(MCI[0:5]): plt.subplot(1,10,index+1) plt.imshow(np.reshape(X_test[misclass],(8,8)), cmap=plt.cm.gray) plt.title("P: {} , A: {} ".format(predictions[misclass],y_test[misclass]))

[@syedriazali1026]

00:01 start watching

[@YasirMehmood-ni1zh]

#17:34 Prediction Spelling Mistake

[@ramizch1739]

from where to get these long codes of matplotlib and seaborn need help thanks in advance🙏

[@AbdulHannan-wf5ye]

17:15 FROM SKLEARN IMPORT METRICS

[@aasimnawaz]

6:46, baba jee the image is not very clear, how we set its quality better

[@rkmofficial202]

started

[@apricotadventure]

Started . Now at 16:28

[@faizaafzal121]

0:00 watching

[@azeemjaved9963]

@20:16 import seaborn as sns

[@azeemjaved9963]

@0:30 started

[@ahsanzafar4921]

Assignment code # finding indexes of data points where model misclassified them misclassified_label = [] for index,(label, prediction) in enumerate(zip(y_test,y_pred)): if label!=prediction: misclassified_label.append(index) # plotting the misclassified labels what they actaully were and what the model predicted them to be plt.figure(figsize=(20,8)) for plotindex,bad_index in enumerate(misclassified_label[:10]): plt.subplot(2,5, plotindex + 1) plt.imshow(np.reshape(X_test[bad_index],(8,8)),cmap=plt.cm.gray) plt.title("Training {}".format(label)) plt.title("Actual {}, Predicted {}".format(y_test[bad_index],y_pred[bad_index]))

[@yasmeenamjad5807]

11 : 55 started

[@hajraanwar8213]

From sklearn import metrics ist.

[@ahmedullah8799]

0:01 startted

[@letsgoo5176]

how can we transfer manual handwritten images to dataset for classification testing ?

[@letsgoo5176]

​@Amir Javaid Thanks, Scanned done .. How to import a hundred images in Python and make Dataset for ML ? Am I missing any lecture?

[@letsgoo5176]

@Amir Javaid The idea is to get handwritten Digit/Alphabet from different people of a different races, age etc to judge/train the system to identify their handwritten, or you may say analyse the different factors involved on such handwritten analysis

[@islamhussain8026]

@@letsgoo5176 simply the way we import other data like csv file. first convert your images to grayscale and then labeled your images like 1,2,3,4,5 and so on. and then put your data into a single folder and provide the path or put in the same folder where your ipynb file is saved and load or read them from there.

[@faizaafzal121]

From sklearn import confusion matrix

[@ahmedullah8799]

0:01 satarted

[@leezatariq2842]

1:39 Watching

[@jmych]

Watching

[@muhammadanwarulhassan6823]

If someone facing this error ""Output exceeds the size limit. Open the full output data in a text editor"" Simply remove cm="Spectral " from the 2nd line of code.

[@Engr.Umair_Mueed]

Hi Mates, I am getting this error while running confusion matric can you please help Found input variables with inconsistent numbers of samples: [360, 10]

[@sanashah4731]

present 51 and 53 video is missing,

[@ashhadahmed72]

16:39: metrics*

[@SoniaAkter-ce9rj]

This error occurs. But why? TypeError Traceback (most recent call last) TypeError: only size-1 arrays can be converted to Python scalars The above exception was the direct cause of the following exception: ValueError Traceback (most recent call last) in () ----> 1 logreg = LogisticRegression().fit(X_train, y_train) 4 frames /usr/local/lib/python3.10/dist-packages/sklearn/utils/_array_api.py in _asarray_with_order(array, dtype, order, copy, xp) 183 if xp.__name__ in {"numpy", "numpy.array_api"}: 184 # Use NumPy API to support order --> 185 array = numpy.asarray(array, order=order, dtype=dtype) 186 return xp.asarray(array, copy=copy) 187 else: ValueError: setting an array element with a sequence.

[@NasirJumani]

For all those who are finding an error, it's somewhere in the second last block. :)

[@hayatop3555]

Yes same

[@mugheezAhmed]

Cant get u guys which line we use back space?

[@NasirJumani]

@@mugheezAhmed index = +1 me indentation error hai

[@MuhammadAswadking]

@@NasirJumani sir problem still not resolved

[@aasimnawaz]

8:35, #split the data , there is typo, here mentioned dat

[@fahadnajeeb6132]

time stamp 20:30 got an error " 'QuadMesh' object has no property 'suqare' " " QuadMesh has no property square while plotting confusion matrix

[@fahadnajeeb6132]

resolved

[@sardarabdullahkhawar8487]

0:0 Watching

[@shoyogamer530]

🥙

[@faizaafzal121]

Import seabron Library

[@asadtariq6080]

started watching

[@technoo2086]

16:44 from sklearn import matrics

[@zeeshanahmed430]

0:00 Started watching

[@hassanorakzai8981]

@16:44 from sklearn import matrics

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17:12 From sklearn import metrics

[@SureshKumar-dw3xs]

17:12 from sklearn import metrics

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17: 10 from sklearn import metrics

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[@muhammadnajamulislam2823]

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[@Fayez-tk7ph]

17:00, from sklearn import metrics

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[@naseerkhan-lu8kn]

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