Getting predictions on the data from Rest API with the model hosted using TensorFlow Serving. — So, you have a beautiful model which works like a charm on the data. Now, you want to put that model in production and get the prediction on new data. Let me introduce to you TensorFlow Serving a system designed to serve trained model in production. By default, it comes…

In the “frozenlake-nonslippery” environment using cross-entropy method to get started with reinforcement learning. — The learning of optimal decision over time by an agent in an environment is generally how reinforcement learning is defined. At a high level there are several methods in reinforcement learning, classified and explained in an oversimplified manner as follows: 1. Model-free or model-based: a. Model-free: Brute force method where agent…

Using Fifa 18 game data, classifying a football player as a CM, ST, CB and GK. — Thanks to ‘Aman Shrivastava’ for sharing the data. We will be using the provided dataset which is processed and ready for the purposes. Use case: As a user, I have statistics of a player and I want to know whether the player should play as a Striker (ST), Center Midfielder…

Level: Beginner Python understanding: Intermediate Knowledge of data science: Intermediate Objective: Develop an intuition of multi-dimensional dataset. Goal: A trained model which does Image Classification IDE: To get started I will recommend using Jupyter notebook on Google Collaboration. Regarded as the hello world of Deep Learning, this dataset exposes inspiring…