Skip to main content

Let's Start The Python


Theory based question:


Why python ? What is Python?


Why python is the best choice for Web based Programming today?
Why python is called interpreted language?

Practical based tutorial:

In these blogs you can learn complex python programs in  easy ways without import any module.

Python program to check if a number is positive, negative or zero



Python program to check if variable is of integer or string



Python program to get the Factorial number of given number







Comments

Popular posts from this blog

Multiple classification from many of directories

  # %%  Import nessacary libraries import  numpy  as  np import  pandas  as  pd import  cv2 import  matplotlib.pyplot  as  plt import  os import  glob # %%   Keras Tensorflow libraries from  keras  import  layers from  keras.models  import  Model from  keras.optimizers  import  RMSprop , Adam , Nadam from  keras.preprocessing.image  import  ImageDataGenerator from  keras.layers  import  Input, BatchNormalization, Dense, Dropout, Conv2D, Flatten, GlobalAveragePooling2D, LeakyReLU from  keras.preprocessing.image  import  ImageDataGenerator, img_to_array, load_img # %%  Path path  =   r 'G:/Machine Learning/Project/Lego Mnifigures Classification/dataset' open_dir  =  os....

Classification & Confusion Matrix & Accuracy Paradox

Classification  work on voting the object belongs from which classes has more probability  There are two types of classification : Binary classification : There are two classes we have ex: male-female , cat-dog , yes-not  Multiple classification :   There are classes more than two we have ex: traffic signs , face recognition , flower race  , Digit Recognition Confusion matrix :  Confusion matrix is one type of technique to evaluate the model accuracy for classification problem. In this technique we consider how many of positive and negative data points we predict correctly. The main consideration terms are accuracy, precision and recall The accuracy was an appealing matric, because it was a single number. Here precision and recall(sensitivity) are two numbers. So to get the final score (accuracy) of our model we use F1 score, so that we have a single number. Here is the F1 score's mathematical formula: F1 = 2x precision x recall / (precision ...

Digit Recognition

Here you can import digit dataset from scikit learn library which is in-built, So you don't need to download from other else Note: If you use visual code, I recommend you to turn your color theme to Monokai because it has a few extra and important keyword and attractive colors than other theme.   # %%  Import libraries import  numpy  as  np import  pandas  as  pd import  matplotlib.pyplot  as  plt import  random  # %%   Load dataset from  sklearn.datasets  import  load_digits dataset  =  load_digits() dataset.keys() output: d ict_keys(['data', 'target', 'target_names', 'images', 'DESCR']) You have to check all to direct print them Here DESCR is a description of dataset # %%   divide the dataset into input and target inputs  =  dataset.data target  =  dataset.target # %% ...