Data Science has received insane Avengers-level hype in the last ~5 years. But did you know that Operations Research (OR) is every bit as fun, rewarding, and challenging? Unlike data science, however, OR isn’t 100% fixated on brute force applying classification and regression to techniques to any and all problems.**I say this a bit tongue and cheek.**But it’s ~true. There are very few tasks that can’t be coerced into classification or regression problems. But let’s shift gears today and discuss some of those problems. Two high impact problems in OR include the “traveling salesman problem” and the “vehicle routing problem.” The latter is much more tricky, involves a time component and often several vehicles. But for this introductory post, let’s focus on the easier of the two.
Consider a salesman who leaves any given location (we’ll say Chicago) and must stop at x other cities before returning home. Wikipedia conveniently lists the top x biggest cities in the US, so we’ll focus on just the top 25.Like any problem, which can be optimized, there must be a cost function. In the context of TSP, total distance traveled must be reduced as much as possible. A brute force solution is 100% possible for only 25 cities, however, it’s deceptively trickier than you might imagine. There are 15,511,210,043,330,985,984,000,000 unique permutations of 25 cities. This is ~15.5 septillion. Did you know septillion was a word?With these many possible combinations, finding the global optimal solution is a bit like finding a hay in a needle stack. (Yes, you read that right.) In response, our goal isn’t to find the global optimal solution — it’s to find one of countless ~near optimal solutions and avoid the countless moderately good (and outright terrible) solutions. Which is a great segue into genetic algorithms.
Genetic algorithms are a class of algorithms that take inspiration from genetics. More specifically, “genes” evolve over several iterations by both crossover (reproduction) and mutation. This will get a bit incest-y, but bear with me. In the simplest case, we start with two genes, these genes interact (crossover) where a new gene is produced receiving some attributes from one gene and the rest from the other. Then, random changes (mutation) are introduced to the new gene. Now there are three genes, two parents and a child; all three are evaluated in terms of a cost function. If the child is the weakest, we delete it and start anew. Otherwise, we remove the weaker of the two parents, then repeat the whole process over with the two remaining genes. _Conceptually, that’ all there is to it._It’s basically make x guesses, create y hybrid guess(es), evaluate the fitness of the gene pool and do some pruning. Rinse and repeat until you converge on a solution. (You will converge on a solution, it just very likely will not be the global optimum.) Yes, because computers are drawing inspiration from genetics, but aren’t intrinsically limited by the characteristics of genetics, the algorithm can have any arbitrary number of parents and children in each iteration.
#python #machine-learning #data-science
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:
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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.
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.
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.
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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
Learn about common algorithm concepts in Python and how to solve algorithm challenges you may encounter in an interview.
⌨️ (0:00:00) Big O Notation
⌨️ (0:22:08) Big O Examples
⌨️ (0:43:01) Array Sequences
⌨️ (0:53:23) Dynamic Arrays
⌨️ (1:06:26) Array Algorithms
⌨️ (1:20:40) Largest Sum
⌨️ (1:31:27) How to Reverse a String
⌨️ (1:57:32) Array Analysis
⌨️ (2:00:00) Array Common Elements
⌨️ (2:28:54) Minesweeper
⌨️ (3:08:16) Frequent Count
⌨️ (3:16:58) Unique Characters in Strings
⌨️ (3:28:35) Non-Repeat Elements in Array
📺 The video in this post was made by freeCodeCamp.org
The origin of the article: https://www.youtube.com/watch?v=p65AHm9MX80&list=PLWKjhJtqVAbnqBxcdjVGgT3uVR10bzTEB&index=8
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Today you’re going to learn how to use Python programming in a way that can ultimately save a lot of space on your drive by removing all the duplicates.
In many situations you may find yourself having duplicates files on your disk and but when it comes to tracking and checking them manually it can tedious.
Heres a solution
Instead of tracking throughout your disk to see if there is a duplicate, you can automate the process using coding, by writing a program to recursively track through the disk and remove all the found duplicates and that’s what this article is about.
But How do we do it?
If we were to read the whole file and then compare it to the rest of the files recursively through the given directory it will take a very long time, then how do we do it?
The answer is hashing, with hashing can generate a given string of letters and numbers which act as the identity of a given file and if we find any other file with the same identity we gonna delete it.
There’s a variety of hashing algorithms out there such as
#python-programming #python-tutorials #learn-python #python-project #python3 #python #python-skills #python-tips