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Tensorflow for Reinforcement Learning

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Reinforcement learning has gained valuable popularity with the relatively recent success of DeepMind's AlphaGo method to beat the world champion Go player. The AlphaGo method was educated in part by reinforcement learning on deep neural networks. This style of learning is a distinct feature of machine learning from the classical supervised and unsupervised paradigms. In reinforcement learning, the network responds to environmental data (called the state) using deep neural networks and influences the behavior of an agent to try to optimize a reward. This technique helps a network to learn how to play sports, such as Atari or other video games, or some other challenge that can be rewritten as a form of the game. In this tutorial, a common model of reinforcement learning, I will introduce the broad principles of Q learning, and I will demonstrate how to incorporate deep Q learning in TensorFlow. Introduction to reinforcement learning As mentioned above, reinforcement learning consis
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Hyperparameter Tuning in Python

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One of the easiest ways to get the last juice out of the models is to pick the right hyperparameters for machine learning or deep learning models. I will show you in this article some of the best ways to do hyperparameter tuning available today (in 2021) Difference between parameter and hyper-parameters? Parameters of the model: These are the parameters calculated on the given dataset by the model. The weights of a deep neural network, for instance. Hyperparameters of Models: these are the parameters where the data model cannot predict. This is used for calculating the parameters of the model. For starters, in deep neural networks the learning rate. Why Hyper-parameter tuning is more important? The tuning technique is used to estimate the best hyperparameter combination that helps the algorithm to optimise the efficiency of the model. The proper hyperparameter combination is the only way to achieve the full value from the models. How to Choose Hyper-parameters? It isn’t a straightforwa
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Location: Aligarh, Uttar Pradesh, India
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What is 100 Days of Code?

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  There were lots of issues and Vagueness with this topic. How will I go for100 days coding all day? How will I code for 1000hrs? Do I have to code the whole 100 days? Will It improve my skills? What are the basic Programming languages I can take for 100 days? And List Continues…. Here, I am to clear your doubts on the 100daysofCode strategy. 100daysofCode challenges you that you will code for at least an hour every day for the next 100 days and it's very skillfully if taken by heart and seriously. It will boost your skills, it will give you enthusiasm to code each day and build your logical section a bit stronger. First, make your mind full set and then decided to make this a public commitment many times and have done 100 days of code a lot with Python, C and C++ as these are my favorite and I want to learn them as well. You can also stick to a single Programming language and can move forward with it if you want to do mastery in it. And you should join me as well and watch my repo
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Location: Aligarh, Uttar Pradesh, India
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