1625085120

onte Carlo Simulation is based on repeated random sampling. The underlying concept of Monte Carlo is to use **randomness **to solve problems that might be deterministic in principle. Monte Carlo simulation is one of the most popular techniques to draw inferences about a population without knowing the true underlying population distribution. This sampling technique becomes handy especially when one doesn’t have the luxury to repeatedly sample from the original population. Applications of Monte Carlo Simulation range from solving problems in theoretical physics to predicting trends in financial investments.

Monte Carlo has 3 main usages: estimate parameters or statistical measures, examine the properties of the estimates, approximate integrals

This article is about these 3 usages of the Monte Carlo procedures and about 3 Monte Carlo variants, statistical sampling techniques, which can be used to generate independent random samples. The article will cover the following topics:

```
- Introduction to Monte Carlo Simulation
- MC Parameter Estimation
- MC Examining the Estimate Properties
- MC Integrals Approximation
- Importance Sampling
- Rejection Sampling
- Inverse Transform Sampling
```

_This article is suited for readers who have prior Statistical knowledge since it will cover medium-level statistical concepts and examples. If you want to learn essential statistical concepts from scratch, you can check my previous article about _*Fundamentals Of Statistics here.*

#machine-learning #programming #monte-carlo #data-science #python #monte carlo simulation and variants with python

1619518440

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

…

#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

1625085120

onte Carlo Simulation is based on repeated random sampling. The underlying concept of Monte Carlo is to use **randomness **to solve problems that might be deterministic in principle. Monte Carlo simulation is one of the most popular techniques to draw inferences about a population without knowing the true underlying population distribution. This sampling technique becomes handy especially when one doesn’t have the luxury to repeatedly sample from the original population. Applications of Monte Carlo Simulation range from solving problems in theoretical physics to predicting trends in financial investments.

Monte Carlo has 3 main usages: estimate parameters or statistical measures, examine the properties of the estimates, approximate integrals

This article is about these 3 usages of the Monte Carlo procedures and about 3 Monte Carlo variants, statistical sampling techniques, which can be used to generate independent random samples. The article will cover the following topics:

```
- Introduction to Monte Carlo Simulation
- MC Parameter Estimation
- MC Examining the Estimate Properties
- MC Integrals Approximation
- Importance Sampling
- Rejection Sampling
- Inverse Transform Sampling
```

_This article is suited for readers who have prior Statistical knowledge since it will cover medium-level statistical concepts and examples. If you want to learn essential statistical concepts from scratch, you can check my previous article about _*Fundamentals Of Statistics here.*

#machine-learning #programming #monte-carlo #data-science #python #monte carlo simulation and variants with python

1619510796

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

1626775355

No programming language is pretty much as diverse as Python. It enables building cutting edge applications effortlessly. Developers are as yet investigating the full capability of end-to-end Python development services in various areas.

By areas, we mean FinTech, HealthTech, InsureTech, Cybersecurity, and that's just the beginning. These are New Economy areas, and Python has the ability to serve every one of them. The vast majority of them require massive computational abilities. Python's code is dynamic and powerful - equipped for taking care of the heavy traffic and substantial algorithmic capacities.

Programming advancement is multidimensional today. Endeavor programming requires an intelligent application with AI and ML capacities. Shopper based applications require information examination to convey a superior client experience. Netflix, Trello, and Amazon are genuine instances of such applications. Python assists with building them effortlessly.

Python can do such numerous things that developers can't discover enough reasons to admire it. Python application development isn't restricted to web and enterprise applications. It is exceptionally adaptable and superb for a wide range of uses.

**Robust frameworks **

Python is known for its tools and frameworks. There's a structure for everything. Django is helpful for building web applications, venture applications, logical applications, and mathematical processing. Flask is another web improvement framework with no conditions.

Web2Py, CherryPy, and Falcon offer incredible capabilities to customize Python development services. A large portion of them are open-source frameworks that allow quick turn of events.

**Simple to read and compose **

Python has an improved sentence structure - one that is like the English language. New engineers for Python can undoubtedly understand where they stand in the development process. The simplicity of composing allows quick application building.

The motivation behind building Python, as said by its maker Guido Van Rossum, was to empower even beginner engineers to comprehend the programming language. The simple coding likewise permits developers to roll out speedy improvements without getting confused by pointless subtleties.

**Utilized by the best **

Alright - Python isn't simply one more programming language. It should have something, which is the reason the business giants use it. Furthermore, that too for different purposes. Developers at Google use Python to assemble framework organization systems, parallel information pusher, code audit, testing and QA, and substantially more. Netflix utilizes Python web development services for its recommendation algorithm and media player.

**Massive community support **

Python has a steadily developing community that offers enormous help. From amateurs to specialists, there's everybody. There are a lot of instructional exercises, documentation, and guides accessible for Python web development solutions.

Today, numerous universities start with Python, adding to the quantity of individuals in the community. Frequently, Python designers team up on various tasks and help each other with algorithmic, utilitarian, and application critical thinking.

**Progressive applications **

Python is the greatest supporter of data science, Machine Learning, and Artificial Intelligence at any enterprise software development company. Its utilization cases in cutting edge applications are the most compelling motivation for its prosperity. Python is the second most well known tool after R for data analytics.

The simplicity of getting sorted out, overseeing, and visualizing information through unique libraries makes it ideal for data based applications. TensorFlow for neural networks and OpenCV for computer vision are two of Python's most well known use cases for Machine learning applications.

Thinking about the advances in programming and innovation, Python is a YES for an assorted scope of utilizations. Game development, web application development services, GUI advancement, ML and AI improvement, Enterprise and customer applications - every one of them uses Python to its full potential.

The disadvantages of Python web improvement arrangements are regularly disregarded by developers and organizations because of the advantages it gives. They focus on quality over speed and performance over blunders. That is the reason it's a good idea to utilize Python for building the applications of the future.

#python development services #python development company #python app development #python development #python in web development #python software development

1602968400

Python is awesome, it’s one of the easiest languages with simple and intuitive syntax but wait, have you ever thought that there might ways to write your python code simpler?

In this tutorial, you’re going to learn a variety of Python tricks that you can use to write your Python code in a more *readable* and *efficient* way like a pro.

**Swapping value in Python**

Instead of creating a **temporary** variable to hold the value of the one while **swapping**, you can do this instead

```
>>> FirstName = "kalebu"
>>> LastName = "Jordan"
>>> FirstName, LastName = LastName, FirstName
>>> print(FirstName, LastName)
('Jordan', 'kalebu')
```

#python #python-programming #python3 #python-tutorials #learn-python #python-tips #python-skills #python-development