FASTAPI | BISP FastAPI | Python Data Science | RESTAPI скачать в хорошем качестве

FASTAPI | BISP FastAPI | Python Data Science | RESTAPI

FastAPI | Data Science with Python | RESTAPI FastAPI is a modern, fast (high-performance), web framework for building APIs with Python based on standard Python type hints. You can achieve expertise in the Data Science field with a lot of real-world scenario and project working experience with the help of our Python fundamentals with data science live project course. This video tutorial basically based on Python web framework i.e. Fast API. How we can create a fast application using fast API. What are Fast API's and its features? After completion of Data Science advanced certification course bisp candidate has better understanding also a good hands-on over the period of training and a live project working associated with. BISP is committed to provide solution to your business problem in a given time frame and we can help you out to turn your strategic plans to exceptional. That can be an enhancement of candidate knowledge over the concepts of Python fundamentals with data science live project. The key features of Python Fast API’s are: Fast Very high performance, on par with NodeJS. One of the fastest Python frameworks available. Fast to code Increase the speed to develop features by about 200% to 300% *. Fewer bugs Reduce about 40% of human (developer) induced errors. Intuitive Great editor support. Completion everywhere. Less time debugging. Easy Designed to be easy to use and learn. Less time reading docs. Short Minimize code duplication. Multiple features from each parameter declaration. Fewer bugs. Robust Get production-ready code. With automatic interactive documentation. Standards-based Based on (and fully compatible with) the open standards for APIs: OpenAPI and JSON Schema. To use an API, you make a request to a remote web server, and retrieve the data you need. APIs are useful in the following cases: • The data is changing quickly. An example of this is stock price data. It doesn’t really make sense to regenerate a datasets and download it every minute — this will take a lot of bandwidth, and be pretty slow. • You want a small piece of a much larger set of data. Reddit comments are one example. What if you want to just pull your own comments on Reddit? It doesn’t make much sense to download the entire Reddit database, then filter just your own comments. • There is repeated computation involved. Spotify has an API that can tell you the genre of a piece of music. You could theoretically create your own classifier, and use it to compute music categories, but you’ll never have as much data as Spotify does. This video provide basics of FASTAPI and how to develop a simple application. It also covers some key features of new generation REST API solution. For complete professional training visit at: Course Details: https://www.bisptrainings.com/Courses... Browse All Courses: https://www.bisptrainings.com/Courses... Email: support@bisptrainings.com Website: https://www.bisptrainings.com For complete professional training visit at https://www.bisptrainings.com/Home Follow us on Facebook:   / bisptrainings   Follow us on Twitter:   / bisptrainings   Follow us on Linkedin:   / admin   Email: support@bisptrainings.com Call us: +91 7694095404 or +1 786-629-6893 #Python #pythonfastapi #datascience #pythonmachinelearning #bisponlinetraining