Reference Counting and Generational Garbage Collection
You are at the right place if you have these questions while learning Python:
- How is memory managed in Python?
- What is garbage collection?
- Which algorithms are used for memory management?
- What is a cyclical reference?
- How are Python objects stored in memory?
Let’s see if I can answer these questions and some more in this article:
I am starting with the fundamentals.
Python Is a Dynamically Typed Language.
We don’t declare the type of a variable when we assign a value to the variable in Python. It states the kind of variable in the runtime of the program. Other languages like C, C++, Java, etc…
Inheritance: Extending Classes To Make New Classes
As you might know, creating a fully functional class in an object-oriented programming language is time-consuming because real classes perform a lot of complex tasks.
In Python, you can get the features you want from an existing class(parent) to create a new class(child). This Python feature is called inheritance.
By inheritance, you can
- obtain the features of a parent class,
- change the features that you don’t need,
- add new features to your child class. (derived class or subclass)
Since you are using a pre-used, tested class, you don’t have to put quite as much effort into your new class. …
Analysis Of Variance(ANOVA)
In this blog, you are going to find answers to the below questions.
- What is ANOVA?
- What are the assumptions of ANOVA?
- In which situations is the ANOVA used?
- What is the difference between Student’s T-test and ANOVA?
What Is ANOVA?
ANOVA is a statistical test that is used to evaluate the difference among the means of three or more groups.
Assumptions of ANOVA
- Populations are normally distributed.
ANOVA can only be applied to data that are normally distributed so we need to run a normality test. However, ANOVA test is robust to the assumption of normality. …
Issues In Knowledge Mining From Data
We are living in the data age. Each second tremendous amounts of data are created, stored, and used in the world. However, the world is rich in data but poor in knowledge. The reason is digging the data to find knowledge is as hard as digging rock to find gold.
When huge data was created from multiple resources, the data mining concept was born.
What Is Data Mining?
Data mining can be simply defined as obtaining valuable knowledge from data. This knowledge can be anomalies, patterns, correlations, and can be used to increase sales, decrease costs, improve customer loyalty, etc.
Major Issues In Data Mining
Transforming data into organized…
A High-Level Overview Of Database Architecture
What is a database?
A database is a systematic collection of data that can easily be accessed, managed, and updated. Databases store a variety of data such as usernames, user IDs, email addresses, etc.
Why databases?
Databases can store, process, and analyze very large numbers of records and turn them into useful information.
When a database is used, data can be searched, sorted, imported easily.
More than one person can access the same database at the same time.
Therefore, our data should be stored elsewhere if we want to reliably access it in the future and, more importantly, share it and work on it with others…
Robotic Process Automation And Artificial Intelligence
When someone wants to download an image from Pixabay, she has to prove that she is not a robot. What is a robot and why this question is asked?
If a human downloads an image from a website it takes a few minutes to find the image, select the rights size, and download it to the local device. It takes only milliseconds to download an image from a website if a robot software is built. This question is asked by Pixabay to make sure that a robot is not downloading all the images from the website.
The below image is…
An Alternative To Google Colab and Jupyter Notebook
Jupyter Notebook
Anyone who works with data makes use of Jupyter notebooks. It is an open-source web application that joins code, output, visualizations, and text. It also organizes your work. Using a Jupyter notebook is a smart solution for individual projects.
Collaborative Notebooks
Anytime you have a project as a team, you need a collaborative tool for real-life collaboration, peer review, or feedback. Google Colab or Kaggle Kernels will help you a lot by making collaboration easier and giving you free or cheap GPU. In this article, I will introduce you to a new notebook called Datalore by JetBrains.
Datalore
Datalore is an online computational…
A Gentle Introduction To Poisson Distribution
A Probability Question
In any 15-minute interval, there is a 20% probability that you will see at least one shooting star. What is the probability that you see at least one shooting star in the period of an hour?
We will solve this question assuming independence of the events.
Solution I: Intuition
A Guide To Feature Selection
What Is Feature Selection?
Imagine that we have a dataset of 1000 columns and millions of rows, how do we decide which columns are more important than the others when we develop a prediction model? The answer is feature selection. By applying some simple and complicated methods, we find the necessary input variables and throw away the noise from the data.
Why do we select features?
You may think that more data results in a better machine learning model. It is true for the number of rows(instances) but not true for the number of columns(features). …
Motivation to become a data scientist
When I decided to switch my career from physics to the data industry, this question was asked me a lot of times by friends and interviewers:
What is your motivation for data science?
I make an attempt to provide an answer to this question and express my passion for data science in this week’s blog.
There are three main reasons to my enthusiasm for data science and analytics.
1. Making The World Better
The first and the most important reason why I have motivation for data science is its power to make things better. Data-driven decision making can be used for comprehensive analysis and future…
