Linear Regression implementation in Python using numpy library.

Github repository:
https://github.com/aladdinpers....son/Machine-Learning

More thorough derivation:
https://aladdinperzon.github.i....o/2020/03/25/Linear-

Welcome to a reinforcement learning tutorial. In this part, we're going to focus on Q-Learning.

Q-Learning is a model-free form of machine learning, in the sense that the AI "agent" does not need to know or have a model of the environment that it will be in. The same algorithm can be used across a variety of environments.

For a given environment, everything is broken down into "states" and "actions." The states are observations and samplings that we pull from the environment, and the actions are the choices the agent has made based on the observation. For the purposes of the rest of this tutorial, we'll use the context of our environment to exemplify how this works.

Text-based tutorial and sample code: https://pythonprogramming.net/....q-learning-reinforce

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#reinforcementlearning #machinelearning #python

OpenAI's Whisper is a speech to text, or automatic speech recognition model. It is a "weakly supervised" encoder-decoder transformer trained on 680,000 hours of audio. Not only can it transcribe English, it can transcribe 96 other languages along with also being able to translate from those languages to English.

Neural Networks from Scratch book: https://nnfs.io
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google colab link
https://colab.research.google.....com/drive/1xyaAMav_g
🤗 Transformers (formerly known as pytorch-transformers and pytorch-pretrained-bert) provides general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet…) for Natural Language Understanding (NLU) and Natural Language Generation (NLG) with over 32+ pretrained models in 100+ languages and deep interoperability between Jax, PyTorch and TensorFlow.
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