In the previous blog, we discussed emotion detection using Keras, in this blog, we’ll develop Cat Vs Dog classification problem. We are going to use the test data from Kaggle website. Kaggle has Dog-Vs-Cat challenge. Let’s start by downloading the data from Kaggle website. Now, we can extract the data and store into test and…
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In the previous blog, we used the TensorFlow high level API to implement the MLP with TensorFlow and in this blog, we’ll implement the same example without using high level api. MLP with TensorFlow Let’s start by downloading the data first using TensorFlow.
Custom Object detection: In the past few blogs, we discussed object detection using ImageAI, TensorFlow and Yolo V3 using CV2, in this blog, we’ll try to use TensorFlow Object detection model to create Custom Object detection model. Create Dataset First, we have to annotate the image and for the learning purpose, I created a custom…
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In the previous blog, we learned how to use the TensorFlow Object detection library to detect the object in the image, in this blog, we’ll implement Live Object Detection using TensorFlow. Before we proceed with code, we have to download model and the TensorFlow Models can be found here: https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.md We’ll use the pre-trained model…
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In the previous few blogs. we discussing the Object detection using ImageAI Library, in this blog, we’ll discuss the Object Detection using TensorFlow. TensorFlow’s Object Detection API is a very powerful tool and can quickly allow to build and deploy powerful image recognition applications. Let’s clone the Tensorflow models: The above command will download the…
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In the previous 67 blogs, we follow the book like Hands-on Machine Learning with Scikit-Learn and TensorFlow, in the blog, we’ll try to use Keras, A high-level API to implement the classic MNIST classification problem. Keras Keras is a high-level API to quickly build and train deep learning models. Keras is useful when you want…
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In the previous few blogs, we are discussing various Reinforcement Learning, in this blog let’s try to play Ms. Pac-Man game using Deep Q-Learning. We’ll use OpenAi gym environments to create Ms. Pac-Man . Below is the piece of code which will create the environment. We’ll use DQN to train our agent. Observation (obs) is nothing but…
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In the previous few blogs, we are discussing various RL examples, in this blog let’s use the Reinforcement Learning to tackle BipedalWalker-v2 task. Let’s understand the task first, as per Gym documentation: Reward is given for moving forward, total 300+ points up to the far end. If the robot falls, it gets -100. Applying motor…
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In the last few blogs, we discussed Reinforcement learning and example, in this blog we discuss another RL-Cart-Pole Task. We’ll use the Open Ai Gym environment to create Cart-Pole environment and train our agent for Cart-Pole Task. Cart-Pole Task As per Open Ai Gym documentation, here is the Cart Pole Task: A pole is attached by an…
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In the previous blog, we discussed a simple armed bandit problem, in this blog, we’ll discuss the multi-armed Bandit problem. In the previous example, we did not consider the states of the bandit and we relied only on action. In this blog, we’ll try to solve the problem which neither fully RL problem or fully…
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