Oleta  Becker

Oleta Becker

1603170000

Generating Suitable ML Models Using LazyPredict Python Tool

While building machine learning models we are not sure which algorithm should work well with the given dataset, hence we end up trying many models and keep iterating until we get proper accuracy. Have you ever thought about getting all the basic algorithms at once to predict for model performance?

LazyPredict is a module helpful for this purpose. LazyPredict will generate all the basic machine learning algorithms’ performances on your model. Along with the accuracy score, LazyPredict provides certain evaluation metrics and the time taken by each model.

Lazypredict is an open-source python package created by Shankar Rao Pandala. Development and contribution to this are still going.

Properties of LazyPredict:

  1. As of now, it is only based on Supervised learning algorithms(Regression and Classification)
  2. Compatible with python version 3.6 and above.
  3. Could be run on Command Line Interface(CLI).
  4. Fast in predicting as all the basic model performances for the dataset is given at once.
  5. Has an inbuilt Pipeline to scaling and transform the data and handle missing values and change categorical data to numeric.
  6. Provides evaluation metrics on individual models.
  7. Shows the time consumed by each model to build.

In this article, I’ll be discussing how to implement LazyPredict for regression and classification models with just a few lines of code.e.

#machine-learning

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Generating Suitable ML Models Using LazyPredict Python Tool
Ray  Patel

Ray Patel

1619518440

top 30 Python Tips and Tricks for Beginners

Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.

1) swap two numbers.

2) Reversing a string in Python.

3) Create a single string from all the elements in list.

4) Chaining Of Comparison Operators.

5) Print The File Path Of Imported Modules.

6) Return Multiple Values From Functions.

7) Find The Most Frequent Value In A List.

8) Check The Memory Usage Of An Object.

#python #python hacks tricks #python learning tips #python programming tricks #python tips #python tips and tricks #python tips and tricks advanced #python tips and tricks for beginners #python tips tricks and techniques #python tutorial #tips and tricks in python #tips to learn python #top 30 python tips and tricks for beginners

Ray  Patel

Ray Patel

1619510796

Lambda, Map, Filter functions in python

Welcome to my Blog, In this article, we will learn python lambda function, Map function, and filter function.

Lambda function in python: Lambda is a one line anonymous function and lambda takes any number of arguments but can only have one expression and python lambda syntax is

Syntax: x = lambda arguments : expression

Now i will show you some python lambda function examples:

#python #anonymous function python #filter function in python #lambda #lambda python 3 #map python #python filter #python filter lambda #python lambda #python lambda examples #python map

Ray  Patel

Ray Patel

1625843760

Python Packages in SQL Server – Get Started with SQL Server Machine Learning Services

Introduction

When installing Machine Learning Services in SQL Server by default few Python Packages are installed. In this article, we will have a look on how to get those installed python package information.

Python Packages

When we choose Python as Machine Learning Service during installation, the following packages are installed in SQL Server,

  • revoscalepy – This Microsoft Python package is used for remote compute contexts, streaming, parallel execution of rx functions for data import and transformation, modeling, visualization, and analysis.
  • microsoftml – This is another Microsoft Python package which adds machine learning algorithms in Python.
  • Anaconda 4.2 – Anaconda is an opensource Python package

#machine learning #sql server #executing python in sql server #machine learning using python #machine learning with sql server #ml in sql server using python #python in sql server ml #python packages #python packages for machine learning services #sql server machine learning services

Generating Suitable ML Models Using LazyPredict Python Tool

While building machine learning models we are not sure which algorithm should work well with the given dataset, hence we end up trying many models and keep iterating until we get proper accuracy. Have you ever thought about getting all the basic algorithms at once to predict for model performance?

https://zcu.io/whxr

#machine-learning #ml #coding #tutorial #python

How To Compare Tesla and Ford Company By Using Magic Methods in Python

Magic Methods are the special methods which gives us the ability to access built in syntactical features such as ‘<’, ‘>’, ‘==’, ‘+’ etc…

You must have worked with such methods without knowing them to be as magic methods. Magic methods can be identified with their names which start with __ and ends with __ like init, call, str etc. These methods are also called Dunder Methods, because of their name starting and ending with Double Underscore (Dunder).

Now there are a number of such special methods, which you might have come across too, in Python. We will just be taking an example of a few of them to understand how they work and how we can use them.

1. init

class AnyClass:
    def __init__():
        print("Init called on its own")
obj = AnyClass()

The first example is _init, _and as the name suggests, it is used for initializing objects. Init method is called on its own, ie. whenever an object is created for the class, the init method is called on its own.

The output of the above code will be given below. Note how we did not call the init method and it got invoked as we created an object for class AnyClass.

Init called on its own

2. add

Let’s move to some other example, add gives us the ability to access the built in syntax feature of the character +. Let’s see how,

class AnyClass:
    def __init__(self, var):
        self.some_var = var
    def __add__(self, other_obj):
        print("Calling the add method")
        return self.some_var + other_obj.some_var
obj1 = AnyClass(5)
obj2 = AnyClass(6)
obj1 + obj2

#python3 #python #python-programming #python-web-development #python-tutorials #python-top-story #python-tips #learn-python