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Machine Learning API development essentials

Track :

Computer Science

Lessons no : 13

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Lessons | 13

Building a Neural Network with PyTorch in 15 Minutes Coding Challenge

Building a Neural Network with PyTorch in 15 Minutes Coding Challenge

Building a Machine Learning API in 15 Minutes Coding Challenge

Building a Machine Learning API in 15 Minutes Coding Challenge

I tried to build a ML Text to Image App with Stable Diffusion in 15 Minutes

I tried to build a ML Text to Image App with Stable Diffusion in 15 Minutes

I tried to build a Machine Learning Python App in 15 Minutes Coding Challenge

I tried to build a Machine Learning Python App in 15 Minutes Coding Challenge

Build a Deep Learning Model that can LIP READ using Python and Tensorflow Full Tutorial

Build a Deep Learning Model that can LIP READ using Python and Tensorflow Full Tutorial

I tried building a AUTO MACHINE LEARNING Web App 15 Minutes

I tried building a AUTO MACHINE LEARNING Web App 15 Minutes

I tried to build a REACT STABLE DIFFUSION App in 15 minutes

I tried to build a REACT STABLE DIFFUSION App in 15 minutes

Building the Gradient Descent Algorithm in 15 Minutes Coding Challenge

Building the Gradient Descent Algorithm in 15 Minutes Coding Challenge

I tried to build a Python Machine Learning Streamlit App in 7 Minutes Coding Challenge

I tried to build a Python Machine Learning Streamlit App in 7 Minutes Coding Challenge

I tried to code a TRAFFIC SIGN ML MODEL in 15 minutes

I tried to code a TRAFFIC SIGN ML MODEL in 15 minutes

I tried coding a AI DEPTH VISION app with MIDAS in 15 Minutes

I tried coding a AI DEPTH VISION app with MIDAS in 15 Minutes

I tried building an ML Cancer Segmentation API in 15 Minutes

I tried building an ML Cancer Segmentation API in 15 Minutes

Jobs From Nick Ask Me ANYTHING Volume 1

Jobs From Nick Ask Me ANYTHING Volume 1

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Machine Learning API development course, in this course is a comprehensive course that guides you through the process of creating, deploying, and managing APIs for machine learning models. In this course, you’ll learn how to design RESTful APIs using frameworks like Flask or FastAPI, integrate machine learning models into APIs, and enable seamless interaction between applications and ML systems. You’ll explore concepts like model serialization, deployment on cloud platforms, handling API requests, and ensuring security and scalability. This hands-on course is perfect for developers and data scientists who want to deploy machine learning solutions effectively and integrate them into real-world applications. By the end, you'll have the skills to build robust APIs that bridge the gap between machine learning models and production-ready systems.