Over 137,000 libraries exist in Python’s repository. So, how do you choose the right one for your machine learning project? A cheat sheet on proven uses can help.
Nothing beats Python in finding solutions to complex mathematical and computational problems. It is a versatile language that can be easily used across domains and is easier to debug too.
45% of tech organizations use Python for their machine learning and AI projects. – Builtwith.com
Python libraries are a work in progress and their use cases and toolkits are continuously advancing. Therefore, AI engineers need to keep a constant tab on the latest developments, more so if they intend to use Python for their machine learning projects.
**Python can be used by beginners and experienced AI Engineers, which makes it a popular choice across levels.
Before we begin with the cheat sheet, please note that Python libraries can be multi-purpose and can be placed in multiple categories. Also, the use of libraries is not constrained to the highlighted tasks.
This cheat sheet aims to help you dig out the best fit.
Top Python Libraries for Deep Learning
We’ve weighed the pros and cons and arrived at these four top picks.
A plug-and-play library with an extensive resource of commonly-used machine learning models and algorithms, TensorFlow comes with facial recognition capabilities. It is one of the biggest open-source Python libraries and a must-have for beginners.
Level: Good for beginners
It runs on top of libraries like CNTK, Theano, and TensorFlow, and offers specific support to deep learning applications. Easier prototyping, modularity, and a user-friendly interface make it an excellent choice for beginners.
Level: Excellent choice for beginners
#python #ai #ml #ai engineers #tensorflow #keras
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
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
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.
#python development services #python development company #python app development #python development #python in web development #python software development
Welcome to my blog, In this article, we will learn the top 20 most useful python modules or packages and these modules every Python developer should know.
Hello everybody and welcome back so in this article I’m going to be sharing with you 20 Python modules you need to know. Now I’ve split these python modules into four different categories to make little bit easier for us and the categories are:
Near the end of the article, I also share my personal favorite Python module so make sure you stay tuned to see what that is also make sure to share with me in the comments down below your favorite Python module.
#python #packages or libraries #python 20 modules #python 20 most usefull modules #python intersting modules #top 20 python libraries #top 20 python modules #top 20 python packages
After simulating real-life events in your restaurant, your restaurant starts to attract more customers so you decided to open chain restaurants at other locations.
Since many customers prefer to eat close by, you want your restaurants to be at most 15 miles away from areas 1, 2, 3, 4, and 5. The optimal solution is to build a minimal number of restaurants that are within 15 miles of all other areas.
Provided that your restaurants can only be placed at areas 1, 2, 3, 4, or 5, which locations should you build your restaurants?
Image by Author
This is called the set covering problem. In this article, you will learn how to solve this problem using CVXPY.
#mathematics #python-programming #optimization #python #how to find best locations for your restaurants with python #find best locations for your restaurants