Let's explore some of the best open source projects by language.
1⃣ Best Python Open Source Projects
🚣♂ TensorFlow
🚣♂ Matplotlib
🚣♂ Flask
🚣♂ Django
🚣♂ PyTorch
2⃣ Best JavaScript Open Source Projects
🚣♂ React
🚣♂ Node.JS
🚣♂ jQuery
3⃣ Best C++ Open Source Projects
🚣♂ Serenity
🚣♂ MongoDB
🚣♂ SonarSource
🚣♂ OBS Studio
🚣♂ Electron
4⃣ Best Java Open Source Projects
🚣♂ Mockito
🚣♂ Realm
🚣♂ Jenkins
🚣♂ Guava
🚣♂ Moshi
It's time to start developing your own open source projects. Explore the projects
1⃣ Best Python Open Source Projects
🚣♂ TensorFlow
🚣♂ Matplotlib
🚣♂ Flask
🚣♂ Django
🚣♂ PyTorch
2⃣ Best JavaScript Open Source Projects
🚣♂ React
🚣♂ Node.JS
🚣♂ jQuery
3⃣ Best C++ Open Source Projects
🚣♂ Serenity
🚣♂ MongoDB
🚣♂ SonarSource
🚣♂ OBS Studio
🚣♂ Electron
4⃣ Best Java Open Source Projects
🚣♂ Mockito
🚣♂ Realm
🚣♂ Jenkins
🚣♂ Guava
🚣♂ Moshi
It's time to start developing your own open source projects. Explore the projects
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Here is an A-Z list of essential programming terms:
1. Array: A data structure that stores a collection of elements of the same type in contiguous memory locations.
2. Boolean: A data type that represents true or false values.
3. Conditional Statement: A statement that executes different code based on a condition.
4. Debugging: The process of identifying and fixing errors or bugs in a program.
5. Exception: An event that occurs during the execution of a program that disrupts the normal flow of instructions.
6. Function: A block of code that performs a specific task and can be called multiple times in a program.
7. GUI (Graphical User Interface): A visual way for users to interact with a computer program using graphical elements like windows, buttons, and menus.
8. HTML (Hypertext Markup Language): The standard markup language used to create web pages.
9. Integer: A data type that represents whole numbers without any fractional part.
10. JSON (JavaScript Object Notation): A lightweight data interchange format commonly used for transmitting data between a server and a web application.
11. Loop: A programming construct that allows repeating a block of code multiple times.
12. Method: A function that is associated with an object in object-oriented programming.
13. Null: A special value that represents the absence of a value.
14. Object-Oriented Programming (OOP): A programming paradigm based on the concept of "objects" that encapsulate data and behavior.
15. Pointer: A variable that stores the memory address of another variable.
16. Queue: A data structure that follows the First-In-First-Out (FIFO) principle.
17. Recursion: A programming technique where a function calls itself to solve a problem.
18. String: A data type that represents a sequence of characters.
19. Tuple: An ordered collection of elements, similar to an array but immutable.
20. Variable: A named storage location in memory that holds a value.
21. While Loop: A loop that repeatedly executes a block of code as long as a specified condition is true.
Best Programming Resources: https://topmate.io/coding/898340
Join for more: https://news.1rj.ru/str/programming_guide
ENJOY LEARNING 👍👍
1. Array: A data structure that stores a collection of elements of the same type in contiguous memory locations.
2. Boolean: A data type that represents true or false values.
3. Conditional Statement: A statement that executes different code based on a condition.
4. Debugging: The process of identifying and fixing errors or bugs in a program.
5. Exception: An event that occurs during the execution of a program that disrupts the normal flow of instructions.
6. Function: A block of code that performs a specific task and can be called multiple times in a program.
7. GUI (Graphical User Interface): A visual way for users to interact with a computer program using graphical elements like windows, buttons, and menus.
8. HTML (Hypertext Markup Language): The standard markup language used to create web pages.
9. Integer: A data type that represents whole numbers without any fractional part.
10. JSON (JavaScript Object Notation): A lightweight data interchange format commonly used for transmitting data between a server and a web application.
11. Loop: A programming construct that allows repeating a block of code multiple times.
12. Method: A function that is associated with an object in object-oriented programming.
13. Null: A special value that represents the absence of a value.
14. Object-Oriented Programming (OOP): A programming paradigm based on the concept of "objects" that encapsulate data and behavior.
15. Pointer: A variable that stores the memory address of another variable.
16. Queue: A data structure that follows the First-In-First-Out (FIFO) principle.
17. Recursion: A programming technique where a function calls itself to solve a problem.
18. String: A data type that represents a sequence of characters.
19. Tuple: An ordered collection of elements, similar to an array but immutable.
20. Variable: A named storage location in memory that holds a value.
21. While Loop: A loop that repeatedly executes a block of code as long as a specified condition is true.
Best Programming Resources: https://topmate.io/coding/898340
Join for more: https://news.1rj.ru/str/programming_guide
ENJOY LEARNING 👍👍
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Top 5 data science concepts 👇
1. Machine Learning: Machine learning is a subset of artificial intelligence that focuses on developing algorithms and models that can learn from and make predictions or decisions based on data. It involves techniques such as supervised learning, unsupervised learning, and reinforcement learning to analyze and interpret patterns in data.
2. Data Visualization: Data visualization is the graphical representation of data to help users understand complex datasets and identify trends, patterns, and insights. It involves creating visualizations such as charts, graphs, maps, and dashboards to communicate data effectively and facilitate data-driven decision-making.
3. Statistical Analysis: Statistical analysis is the process of collecting, exploring, analyzing, and interpreting data to uncover patterns, relationships, and trends. It involves using statistical methods such as hypothesis testing, regression analysis, and probability theory to draw meaningful conclusions from data and make informed decisions.
4. Data Preprocessing: Data preprocessing is the initial step in the data analysis process that involves cleaning, transforming, and preparing raw data for analysis. It includes tasks such as data cleaning, feature selection, normalization, and handling missing values to ensure the quality and reliability of the data before applying machine learning algorithms.
5. Big Data: Big data refers to large and complex datasets that exceed the processing capabilities of traditional data management tools. It involves storing, processing, and analyzing massive volumes of structured and unstructured data to extract valuable insights and drive informed decision-making. Techniques such as distributed computing, parallel processing, and cloud computing are used to handle big data efficiently.
Data Science Resources for Beginners
👇👇
https://drive.google.com/drive/folders/1uCShXgmol-fGMqeF2hf9xA5XPKVSxeTo
Share with credits: https://news.1rj.ru/str/datasciencefun
ENJOY LEARNING 👍👍
1. Machine Learning: Machine learning is a subset of artificial intelligence that focuses on developing algorithms and models that can learn from and make predictions or decisions based on data. It involves techniques such as supervised learning, unsupervised learning, and reinforcement learning to analyze and interpret patterns in data.
2. Data Visualization: Data visualization is the graphical representation of data to help users understand complex datasets and identify trends, patterns, and insights. It involves creating visualizations such as charts, graphs, maps, and dashboards to communicate data effectively and facilitate data-driven decision-making.
3. Statistical Analysis: Statistical analysis is the process of collecting, exploring, analyzing, and interpreting data to uncover patterns, relationships, and trends. It involves using statistical methods such as hypothesis testing, regression analysis, and probability theory to draw meaningful conclusions from data and make informed decisions.
4. Data Preprocessing: Data preprocessing is the initial step in the data analysis process that involves cleaning, transforming, and preparing raw data for analysis. It includes tasks such as data cleaning, feature selection, normalization, and handling missing values to ensure the quality and reliability of the data before applying machine learning algorithms.
5. Big Data: Big data refers to large and complex datasets that exceed the processing capabilities of traditional data management tools. It involves storing, processing, and analyzing massive volumes of structured and unstructured data to extract valuable insights and drive informed decision-making. Techniques such as distributed computing, parallel processing, and cloud computing are used to handle big data efficiently.
Data Science Resources for Beginners
👇👇
https://drive.google.com/drive/folders/1uCShXgmol-fGMqeF2hf9xA5XPKVSxeTo
Share with credits: https://news.1rj.ru/str/datasciencefun
ENJOY LEARNING 👍👍
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Python Projects
Face Recognition Python Project: Click Here!
How to make Jarvis in Python: Click Here!
Python Chatbot Tutorial: Click Here!
Simple Student Result Database System: Click Here!
Don't Forget to like & share it with your friends.
Face Recognition Python Project: Click Here!
How to make Jarvis in Python: Click Here!
Python Chatbot Tutorial: Click Here!
Simple Student Result Database System: Click Here!
Don't Forget to like & share it with your friends.
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Python Constructs
1. Functions in Python
A function in Python is a collection of statements grouped under a name. You can use it whenever you want to execute all those statements at a time.
You can call it wherever you want and as many times as you want in a program. A function may return a value.
2. Classes in Python
Python is an object-oriented language. It supports classes and objects.
A class is an abstract data type. In other words, it is a blueprint for an object of a certain kind. It holds no values.
An object is a real-world entity and an instance of a class.
3. Modules in Python
Python module is a collection of related classes and functions.
We have modules for mathematical calculations, string manipulations, web programming, and many more.
4. Packages in Python
Python package is a collection of related modules. You can either import a package or create your own.
Python has a lot of other constructs. These include control structures, functions, exceptions, etc
1. Functions in Python
A function in Python is a collection of statements grouped under a name. You can use it whenever you want to execute all those statements at a time.
You can call it wherever you want and as many times as you want in a program. A function may return a value.
2. Classes in Python
Python is an object-oriented language. It supports classes and objects.
A class is an abstract data type. In other words, it is a blueprint for an object of a certain kind. It holds no values.
An object is a real-world entity and an instance of a class.
3. Modules in Python
Python module is a collection of related classes and functions.
We have modules for mathematical calculations, string manipulations, web programming, and many more.
4. Packages in Python
Python package is a collection of related modules. You can either import a package or create your own.
Python has a lot of other constructs. These include control structures, functions, exceptions, etc
👉 What is Python Data Structures?
You can think of a data structure as a way of organizing and storing data such that we can access and modify it efficiently.
We have primitive data types like integers, floats, Booleans, and strings.
👉 What is Python List?
A list in Python is a heterogeneous container for items. This would remind you of an array in C++, but since Python does not support arrays, we have Python Lists.
👉 Python Tuple
This Python Data Structure is like a, like a list in Python, is a heterogeneous container for items.
But the major difference between the two (tuple and list) is that a list is mutable, but a tuple is immutable.
This means that while you can reassign or delete an entire tuple, you cannot do the same to a single item or a slice.
👉 Python Dictionaries
Finally, we will take a look at Python dictionaries. Think of a real-life dictionary. What is it used for? It holds word-meaning pairs. Likewise, a Python dictionary holds key-value pairs. However, you may not use an unhashable item as a key.
To declare a Python dictionary, we use curly braces. But since it has key-value pairs instead of single values, this differentiates a dictionary from a set.
You can think of a data structure as a way of organizing and storing data such that we can access and modify it efficiently.
We have primitive data types like integers, floats, Booleans, and strings.
👉 What is Python List?
A list in Python is a heterogeneous container for items. This would remind you of an array in C++, but since Python does not support arrays, we have Python Lists.
👉 Python Tuple
This Python Data Structure is like a, like a list in Python, is a heterogeneous container for items.
But the major difference between the two (tuple and list) is that a list is mutable, but a tuple is immutable.
This means that while you can reassign or delete an entire tuple, you cannot do the same to a single item or a slice.
👉 Python Dictionaries
Finally, we will take a look at Python dictionaries. Think of a real-life dictionary. What is it used for? It holds word-meaning pairs. Likewise, a Python dictionary holds key-value pairs. However, you may not use an unhashable item as a key.
To declare a Python dictionary, we use curly braces. But since it has key-value pairs instead of single values, this differentiates a dictionary from a set.
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What is Python Loop?
When you want some statements to execute a hundred times, you don’t repeat them 100 times.
Think of when you want to print numbers 1 to 99. Or that you want to say Hello to 99 friends.
In such a case, you can use loops in python.
Here, we will discuss 4 types of Python Loop:
Python For Loop
Python While Loop
Python Loop Control Statements
Nested For Loop in Python
Python While Loop
A while loop in python iterates till its condition becomes False. In other words, it executes the statements under itself while the condition it takes is True.
Python For Loop
Python for loop can iterate over a sequence of items. The structure of a for loop in Python is different than that in C++ or Java.
That is, for(int i=0;i<n;i++) won’t work here. In Python, we use the ‘in’ keyword.
Nested for Loops in Python
You can also nest a loop inside another. You can put a for loop inside a while, or a while inside a for, or a for inside a for, or a while inside a while.
Or you can put a loop inside a loop inside a loop. You can go as far as you want.
Loop Control Statements in Python
Sometimes, you may want to break out of normal execution in a loop.
For this, we have three keywords in Python- break, continue, and Python
When you want some statements to execute a hundred times, you don’t repeat them 100 times.
Think of when you want to print numbers 1 to 99. Or that you want to say Hello to 99 friends.
In such a case, you can use loops in python.
Here, we will discuss 4 types of Python Loop:
Python For Loop
Python While Loop
Python Loop Control Statements
Nested For Loop in Python
Python While Loop
A while loop in python iterates till its condition becomes False. In other words, it executes the statements under itself while the condition it takes is True.
Python For Loop
Python for loop can iterate over a sequence of items. The structure of a for loop in Python is different than that in C++ or Java.
That is, for(int i=0;i<n;i++) won’t work here. In Python, we use the ‘in’ keyword.
Nested for Loops in Python
You can also nest a loop inside another. You can put a for loop inside a while, or a while inside a for, or a for inside a for, or a while inside a while.
Or you can put a loop inside a loop inside a loop. You can go as far as you want.
Loop Control Statements in Python
Sometimes, you may want to break out of normal execution in a loop.
For this, we have three keywords in Python- break, continue, and Python
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