ஆற்காடு சுற்றுலா

 Windows 10 and MS Office 2020 Short cut keys CTRL+A. . . . . . . . . . . . . . . . . Select All CTRL+C. . . . . . . . . . . . . . . . . Copy CTRL+X. . . . . . . . . . . . . . . . . Cut CTRL+V. . . . . . . . . . . . . . . . . Paste CTRL+Z. . . . . . . . . . . . . . . . . Undo CTRL+B. . . . . . . . . . . . . . . . . Bold CTRL+U. . . . . . . . . . . . . . . . . Underline CTRL+I . . . . . . . . . . . . . . . . . Italic F1 . . . . . . . . . . . . . . . . . . . . . . Help F2 . . . . . . . . . . . . . . . . . . . . . Rename selected object F3 . . . . . . . . . . . . . . . . . . . . . Find all files F4 . . . . . . . . . . . . . . . . . . . . . Opens file list drop-down in dialogs F5 . . . . . . . . . . . . . . . . . . . . . Refresh current window F6 . . . . . . . . . . . . . . . . . . . . . Shifts focus in Windows Explorer F10 . . . . . . . . . . . . . . . . . . . . Activates menu bar options ALT+TAB . . . . . . . . . . . . . . . . Cycles between open applications ALT+F4 . . . . . . . . . . .

 Most Viewed Youtube videos in Past 1 day 1. Youtube Top Video Ranks by Viewers Kworb is the popular and most famous website like Alexa ranks the youtube videos. For example, today as of writing this article the most viewed youtube video is  Maluma Album    which is viewed my nearly 1 crore viewers in 1 day of posting.   2. Taaron Ke Shehar song This song reaches 16 crores Indian hearts, ranks number 1 video in India. Song is sung by Neha Nakkar and Sunnil Kaushal. Don't miss to watch this song on Youtube   Taaron Ke Shehar   3. Music for all Once upon a time to listen to this song We have to pay Rs. 100/- per album, that to available only in Metro cities. But bcoz of Video On Deman and Pay Per View model, now available in Indian towns also. I remember the days, we watched this new songs in Chitrahar, on Doordharshan II, Beta songs 'Tak Taku milnae Ragha...'  

Imagenet Dataset and Image Recognition   import  tensorflow  as  tf from  tensorflow  import  keras from  keras.models  import  Sequential from  keras.layers  import  Dense, Flatten, Conv2D, MaxPooling2D, Dropout from  tensorflow.keras  import  layers from  keras.utils  import  to_categorical import  numpy  as  np import  matplotlib.pyplot  as  plt plt.style.use( 'fivethirtyeight' )   from  keras.datasets  import  cifar10 (x_train, y_train),(x_test, y_test) = cifar10.load_data()   plt.imshow(x_train[ 0 ])   y_train_one_hot = to_categorical(y_train) y_test_one_hot = to_categorical(y_test) x_train = x_train/ 255 x_test = x_test/ 255   model = Sequential() model.add(Conv2D( 32 ,( 5 , 5 ),activation= 'relu' , input_shape=( 32 , 32 , 3 ))) model.add(MaxPooling2D(pool_size=( 2 , 2 ))) model.add(Conv2D( 32 ,( 5 , 5 ),activation= 'relu' )) model.add(MaxPooling2D(pool_size=( 2 , 2 ))) model.add(Flatten()) model.add(Dense( 1000 ,activation= 'relu' )) model.add(Dro

 70,000 MNIST Hand  Writing Recognition - Logistic Regression  from sklearn.datasets import fetch_openml mnist = fetch_openml('mnist_784') x,y = mnist['data'],mnist['target'] x,y = mnist['data'], mnist['target'] import  matplotlib.pyplot  as  plt some_digit = x_test[ 2813 ] some_digit_image = some_digit.reshape( 28 , 28 )   plt.imshow(some_digit_image)   x_train, x_test = x[: 60000 ], x[ 60000 :] y_train, y_test = y[: 60000 ], y[ 60000 :] import  numpy  as  np shuffle_index = np.random.permutation( 60000 ) x_train, y_train = x_train[shuffle_index], y_train[shuffle_index]     from  sklearn.linear_model  import  LogisticRegression clf = LogisticRegression() clf.fit(x_train, y_train)   some1 = x_test[ 2813 ] some1.reshape( 28 , 28 ) clf.predict([some1])    Colab Notebook Link:  MNIST Colab Notebook