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15 Python Tips : How to Write Code Effectively

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 Here are some Python tips to keep in mind that will help you write clean, efficient, and bug-free code.     Python Tips for Effective Coding 1. Code Readability and PEP 8  Always aim for clean and readable code by following PEP 8 guidelines.  Use meaningful variable names, avoid excessively long lines (stick to 79 characters), and organize imports properly. 2. Use List Comprehensions List comprehensions are concise and often faster than regular for-loops. Example: squares = [x**2 for x in range(10)] instead of creating an empty list and appending each square value. 3. Take Advantage of Python’s Built-in Libraries  Libraries like itertools, collections, math, and datetime provide powerful functions and data structures that can simplify your code.   For example, collections.Counter can quickly count elements in a list, and itertools.chain can flatten nested lists. 4. Use enumerate Instead of Range     When you need both the index and the value in a loop, enumerate is a more Pyth

2 Top Python Libraries to Create ML model

To Create a Model of Machine Learning in Python, you need TWO libraries. One is 'NUMPY' and the other one is 'PANDAS'.


Libraries You Need to Create ML Model

2 Top Libraries You Need


To Build a model of Machine learning you need the right kind of data. So, use the data for your project should be refined. Else, it will not produce correct results. The prime steps are Data Analysis and Data Preprocessing.

  1. NUMPY - It has the capabilities of Calculations.
  2. PANDAS- It has the capabilities of Data processing.

How Install Python Machine Learning Libraries 

import NumPy as np # linear algebra
import pandas as PD # data processing, CSV file I/O (e.g. PD.read_csv)


How to Check NumPy/Pandas installed

After '.' you need to give double underscore on both sides of the version. 

how to check numpy or pandas version


How Many Types of Data You Need

You need two types of data. One is data to build a model and the other one is data you need to test the model.
  1. Raw data
  2. Evaluate-data


How to Build a Model Flowchart

I have given a flowchart to build a model along with sample data.


Comments

  1. Big data solutions developer should understand the need of Data, and they should work to build more appropriate services to meet the requirements of their clients.


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