Adventuresinmachinelearning.com

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Adventures in Machine Learning – Get ready for your ...

Adventuresinmachinelearning.com Updated for TensorFlow 2 Google’s TensorFlow has been a hot topic in deep learning recently. The open source software, designed to allow efficient computation …

NLP – Adventures in Machine Learning

Adventuresinmachinelearning.com Understanding Word2Vec word embedding is a critical component in your machine learning journey. Word embedding is a necessary step in performing efficient natural language processing in …

Neural Networks Tutorial – A Pathway to Deep Learning ...

Adventuresinmachinelearning.com As can be seen in the figure above, the function is “activated” i.e. it moves from 0 to 1 when the input x is greater than a certain value. The sigmoid function isn’t a step function however, the edge is “soft”, and the output doesn’t change instantaneously.

A PyTorch tutorial – deep learning in Python – Adventures ...

Adventuresinmachinelearning.com Oct 26, 2017  · So – if you’re a follower of this blog and you’ve been trying out your own deep learning networks in TensorFlow and Keras, you’ve probably come across the somewhat frustrating business of debugging these deep learning libraries.Sure, they have Python APIs, but it’s kinda hard to figure out what exactly is happening when something goes wrong.

Coding the Deep Learning Revolution – Adventures in ...

Adventuresinmachinelearning.com Coding the Deep Learning Revolution – Adventures in ...

Reinforcement learning tutorial using Python and Keras ...

Adventuresinmachinelearning.com def naive_sum_reward_agent(env, num_episodes=500): # this is the table that will hold our summated rewards for # each action in each state r_table = np.zeros((5, 2)) for g in range(num_episodes): s = env.reset() done = False while not done: if np.sum(r_table[s, :]) == 0: # make a random selection of actions a = np.random.randint(0, 2) else: # select the action with highest cummulative reward a ...

An introduction to Global Average Pooling in convolutional ...

Adventuresinmachinelearning.com def naive_sum_reward_agent(env, num_episodes=500): # this is the table that will hold our summated rewards for # each action in each state r_table = np.zeros((5, 2)) for g in range(num_episodes): s = env.reset() done = False while not done: if np.sum(r_table[s, :]) == 0: # make a random selection of actions a = np.random.randint(0, 2) else: # select the action with highest cummulative reward a ...

Keras, Eager and TensorFlow 2.0 – a new TF paradigm ...

Adventuresinmachinelearning.com Oct 04, 2018  · A recent announcement from the TensorFlow development team has informed the world that some major new changes are coming to TensorFlow, resulting …

An introduction to entropy, cross entropy and KL ...

Adventuresinmachinelearning.com Oct 04, 2018  · A recent announcement from the TensorFlow development team has informed the world that some major new changes are coming to TensorFlow, resulting …

SumTree introduction in Python – Adventures in Machine ...

Adventuresinmachinelearning.com Oct 04, 2018  · A recent announcement from the TensorFlow development team has informed the world that some major new changes are coming to TensorFlow, resulting …

Python gensim Word2Vec tutorial with TensorFlow and Keras ...

Adventuresinmachinelearning.com The required input to the gensim Word2Vec module is an iterator object, which sequentially supplies sentences from which gensim will train the embedding layer.The line above shows the supplied gensim iterator for the text8 corpus, but below shows another generic form that could be used in its place for a different data set (not actually implemented in the code for this tutorial), where the ...

Reinforcement learning – Adventures in Machine Learning

Adventuresinmachinelearning.com In previous posts (here and here), I have been covering policy gradient-based reinforcement learning methods. In this post, I will continue the series by covering another pseudo-policy gradient based method called Proximal Policy Optimization (PPO).…

Contact - Adventures in Machine Learning

Adventuresinmachinelearning.com We use cookies to ensure that we give you the best experience on our website. If you continue to use this site we will assume that you are happy with it.

Atari Space Invaders and Dueling Q RL in TensorFlow 2 ...

Adventuresinmachinelearning.com Nov 15, 2019  · In previous posts (here and here) I introduced Double Q learning and the Dueling Q architecture.These followed on from posts about deep Q learning, and showed how double Q and dueling Q learning is superior to vanilla deep Q learning. However, these posts only included examples of simplistic environments like the OpenAI Cartpole environment. These types of environments are good …

Adventures in Machine Learning - Learn and explore machine ...

Adventuresinmachinelearning.com Adventures in Machine Learning - Learn and explore machine ...

Thanks for buying Coding the Deep Learning Revolution ...

Adventuresinmachinelearning.com Please check your e-mail – you will be receiving your link to download the eBook file and the Python code files shortly. If you don’t receive the files, please ...

Cart - Adventures in Machine Learning

Adventuresinmachinelearning.com We use cookies to ensure that we give you the best experience on our website. If you continue to use this site we will assume that you are happy with it.

Recurrent neural networks and LSTM tutorial in Python and ...

Adventuresinmachinelearning.com Oct 09, 2017  · In the diagram above, we have a simple recurrent neural network with three input nodes. These input nodes are fed into a hidden layer, with sigmoid activations, as per any normal densely connected neural network.What happens next is what is interesting – the output of the hidden layer is then fed back into the same hidden layer. As you can see the hidden layer outputs are passed …

About – Adventures in Machine Learning

Adventuresinmachinelearning.com Blog Posts. I am a fashion photographer and blogger, feel free to read the whole story. Whereas a trend often connotes a very specific aesthetic expression, and often lasting shorter than a season.

News – Adventures in Machine Learning

Adventuresinmachinelearning.com This is an example page. It’s different from a blog post because it will stay in one place and will show up in your site navigation (in most themes).

Contact me – Adventures in Machine Learning

Adventuresinmachinelearning.com social Follow. Connect on social. I am a fashion photographer and blogger, feel free to read the whole story. Whereas a trend often connotes.

Keras tutorial – build a convolutional neural network in ...

Adventuresinmachinelearning.com May 17, 2017  · In a previous tutorial, I demonstrated how to create a convolutional neural network (CNN) using TensorFlow to classify the MNIST handwritten digit dataset. TensorFlow is a brilliant tool, with lots of power and flexibility. However, for quick prototyping work it can be a bit verbose. Enter Keras and this Keras tutorial. Keras is a higher level library which operates over either TensorFlow or ...

Double Q – Adventures in Machine Learning

Adventuresinmachinelearning.com In this post, we’ll be covering Dueling Q networks for reinforcement learning in TensorFlow 2. This reinforcement learning architecture is an improvement on the Double Q …

PPO – Adventures in Machine Learning

Adventuresinmachinelearning.com Mar 29, 2021  · In previous posts (here and here), I have been covering policy gradient-based reinforcement learning methods. In this post, I will continue the series by covering another pseudo-policy gradient based method called Proximal Policy Optimization (PPO).…

Weight initialization – Adventures in Machine Learning

Adventuresinmachinelearning.com In the late 80’s and 90’s, neural network research stalled due to a lack of good performance. There were a number of reasons for this, outlined by the prominent AI researcher Geoffrey Hinton – these reasons included poor computing speeds, lack of data, using the wrong type of non-linear activation functions and poor initialization of the…

TensorFlow – Page 2 – Adventures in Machine Learning

Adventuresinmachinelearning.com It’s a great time to be practising deep learning. The main existing deep learning frameworks like TensorFlow, Keras and PyTorch are maturing and offer a lot of …

Cross entropy Archives - Adventures in Machine Learning

Adventuresinmachinelearning.com An introduction to entropy, cross entropy and KL divergence in machine learning. By admin | Cross entropy , Deep learning , Loss functions , PyTorch , TensorFlow If you've been involved with neural networks and have beeen using them for classification, you almost certainly will have used a cross entropy loss function.

Transfer learning Archives - Adventures in Machine Learning

Adventuresinmachinelearning.com What are the benefits of transfer learning? Transfer learning has many benefits, these are: It speeds up learning: For state of the art results in deep learning, one often needs to build very deep networks with many layers.In order to train such networks, one needs lots of data, computational power and time.

A2C Archives - Adventures in Machine Learning

Adventuresinmachinelearning.com A2C Advantage Actor Critic in TensorFlow 2. By admin | A2C , Reinforcement learning , TensorFlow 2.0 In a previous post, I gave an introduction to Policy Gradient reinforcement learning.Policy gradient-based reinforcement learning relies on using neural networks to learn an action policy for the control of agents in …

TensorBoard Archives - Adventures in Machine Learning

Adventuresinmachinelearning.com Visualizing the graph in TensorBoard. As you are likely to be aware, TensorFlow calculations are performed in the context of a computational graph (if you're not aware of this, check out my TensorFlow tutorial).To communicate the structure of your network, and to check it for complicated networks, it is useful to be able to visualize the computational graph.

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