Categories
Jekyll
Reinforcement Learning Explained Visually - Model-free solutions, step-by-step
A Visual Guide to techniques used by Value-based and Policy-based solutions, in Plain English.
In Jekyll, tutorial, Feb 02, 2019
tutorial
Enterprise ML - Why putting your model in production takes longer than building it
A Gentle Guide to Enterprise, in Plain English
In Neural, tutorial, Jun 28, 2021
Transformers Explained Visually - Not just how, but Why they work so well
A Gentle Guide to how the Attention Score calculations capture relationships between words in a sequence, in Plain English.
In Transformers, tutorial, Jun 02, 2021
Batch Norm Explained Visually - Why does it work?
A Gentle Guide to the reasons for the Batch Norm layer's success in making training converge faster, in Plain English
In Neural, tutorial, May 27, 2021
Differential and Adaptive Learning Rates - Neural Network Optimizers and Schedulers demystified
A Gentle Guide to boosting model training and hyperparameter tuning with Optimizers and Schedulers, in Plain English
In Neural, tutorial, May 22, 2021
Batch Norm Explained Visually — How it works, and why neural networks need it
A Gentle Guide to an all-important Deep Learning layer, in Plain English
In Neural, tutorial, May 10, 2021
Foundations of NLP Explained — Bleu Score and WER Metrics
A Gentle Guide to two essential metrics (Bleu Score and Word Error Rate) for NLP models, in Plain English
In NLP, tutorial, May 07, 2021
Image Captions with Attention in Tensorflow, Step-by-step
An end-to-end example using Encoder-Decoder with Attention in Keras and Tensorflow 2.0, in Plain English
In Vision, tutorial, Apr 27, 2021
Image Captions with Deep Learning - State-of-the-Art Architectures
A Gentle Guide to Image Feature Encoders, Sequence Decoders, Attention, and Multimodal Architectures, in Plain English
In Vision, tutorial, Apr 20, 2021
Leveraging GeoLocation Data with Machine Learning - Essential Techniques
A Gentle Guide to Feature Engineering and Visualization with Geolocation Data, in Plain English
In GeoLocation, tutorial, Apr 11, 2021
Neural Network Optimizers Made Simple - Core algorithms and why they are needed
A Gentle Guide to fundamental techniques used by gradient descent optimizers like SGD, Momentum, RMSProp, Adam, and others, in plain English.
In Optimizer, tutorial, Apr 07, 2021
Foundations of NLP Explained Visually - Beam Search, How It Works
A gentle guide to how Beam Search enhances predictions, in plain English
In NLP, tutorial, Apr 01, 2021
Audio Deep Learning Made Simple - Automatic Speech Recognition (ASR), How it Works
Speech-to-Text algorithm and architecture, including Mel Spectrograms, MFCCs, CTC Loss and Decoder, in Plain English.
In Audio, tutorial, Mar 26, 2021
Audio Deep Learning Made Simple - Sound Classification, Step-by-Step
An end-to-end example and architecture for audio deep learning’s foundational application scenario, in plain English.
In Audio, tutorial, Mar 18, 2021
Audio Deep Learning Made Simple - Data Preparation and Augmentation
A Gentle Guide to enhancing Spectrogram features for optimal performance. Also Data Augmentation, in Plain English.
In Audio, tutorial, Feb 24, 2021
Audio Deep Learning Made Simple - Why Mel Spectrograms perform better
A Gentle Guide to processing audio in Python. What are Mel Spectrograms and how to generate them, in Plain English.
In Audio, tutorial, Feb 19, 2021
Audio Deep Learning Made Simple - State-of-the-Art Techniques
A Gentle Guide to the world of disruptive deep learning audio applications and architectures. And why we all need to know about Spectrograms, in Plain English.
In Audio, tutorial, Feb 12, 2021
Transformers Explained Visually - Multi-head Attention, deep dive
A Gentle Guide to the inner workings of Self-Attention, Encoder-Decoder Attention, Attention Score and Masking, in Plain English.
In Transformers, tutorial, Jan 17, 2021
Transformers Explained Visually - How it works, step-by-step
A Gentle Guide to the Transformer under the hood, and its end-to-end operation.
In Transformers, tutorial, Jan 02, 2021
Reinforcement Learning Explained Visually - Policy Gradients, step-by-step
A Gentle Guide to the REINFORCE algorithm, in Plain English.
In Reinforcement Learning, tutorial, Dec 30, 2020
Transformers Explained Visually - Overview of Functionality
A Gentle Guide to Transformers, how they are used for NLP, and why they are better than RNNs, in Plain English. How Attention helps improve performance.
In Transformers, tutorial, Dec 13, 2020
Reinforcement Learning Explained Visually - Deep Q Networks, step-by-step
A Gentle Guide to DQNs with Experience Replay, in Plain English.
In Reinforcement Learning, tutorial, Nov 30, 2020
Reinforcement Learning Explained Visually - Q Learning, step-by-step
A Visual Guide to how and why the Q Learning Algorithm works, in Plain English.
In Reinforcement Learning, tutorial, Nov 15, 2020
Reinforcement Learning Made Simple - Solution Approaches
A Gentle Overview of RL solutions, and how to categorize them. Important takeaways from the Bellman equation, in Plain English.
In Reinforcement Learning, tutorial, Feb 02, 2019
Reinforcement Learning Explained Visually - Model-free solutions, step-by-step
A Visual Guide to techniques used by Value-based and Policy-based solutions, in Plain English.
In Jekyll, tutorial, Feb 02, 2019
Reinforcement Learning Made Simple - Intro to Basic Concepts and Terminology
A Gentle Guide to applying Markov Decision Processes, in Plain English.
In Reinforcement Learning, tutorial, Feb 02, 2019
Reinforcement Learning
Reinforcement Learning Explained Visually - Policy Gradients, step-by-step
A Gentle Guide to the REINFORCE algorithm, in Plain English.
In Reinforcement Learning, tutorial, Dec 30, 2020
Reinforcement Learning Explained Visually - Deep Q Networks, step-by-step
A Gentle Guide to DQNs with Experience Replay, in Plain English.
In Reinforcement Learning, tutorial, Nov 30, 2020
Reinforcement Learning Explained Visually - Q Learning, step-by-step
A Visual Guide to how and why the Q Learning Algorithm works, in Plain English.
In Reinforcement Learning, tutorial, Nov 15, 2020
Reinforcement Learning Made Simple - Solution Approaches
A Gentle Overview of RL solutions, and how to categorize them. Important takeaways from the Bellman equation, in Plain English.
In Reinforcement Learning, tutorial, Feb 02, 2019
Reinforcement Learning Made Simple - Intro to Basic Concepts and Terminology
A Gentle Guide to applying Markov Decision Processes, in Plain English.
In Reinforcement Learning, tutorial, Feb 02, 2019
Transformers
Transformers Explained Visually - Not just how, but Why they work so well
A Gentle Guide to how the Attention Score calculations capture relationships between words in a sequence, in Plain English.
In Transformers, tutorial, Jun 02, 2021
Transformers Explained Visually - Multi-head Attention, deep dive
A Gentle Guide to the inner workings of Self-Attention, Encoder-Decoder Attention, Attention Score and Masking, in Plain English.
In Transformers, tutorial, Jan 17, 2021
Transformers Explained Visually - How it works, step-by-step
A Gentle Guide to the Transformer under the hood, and its end-to-end operation.
In Transformers, tutorial, Jan 02, 2021
Transformers Explained Visually - Overview of Functionality
A Gentle Guide to Transformers, how they are used for NLP, and why they are better than RNNs, in Plain English. How Attention helps improve performance.
In Transformers, tutorial, Dec 13, 2020
Audio
Audio Deep Learning Made Simple - Automatic Speech Recognition (ASR), How it Works
Speech-to-Text algorithm and architecture, including Mel Spectrograms, MFCCs, CTC Loss and Decoder, in Plain English.
In Audio, tutorial, Mar 26, 2021
Audio Deep Learning Made Simple - Sound Classification, Step-by-Step
An end-to-end example and architecture for audio deep learning’s foundational application scenario, in plain English.
In Audio, tutorial, Mar 18, 2021
Audio Deep Learning Made Simple - Data Preparation and Augmentation
A Gentle Guide to enhancing Spectrogram features for optimal performance. Also Data Augmentation, in Plain English.
In Audio, tutorial, Feb 24, 2021
Audio Deep Learning Made Simple - Why Mel Spectrograms perform better
A Gentle Guide to processing audio in Python. What are Mel Spectrograms and how to generate them, in Plain English.
In Audio, tutorial, Feb 19, 2021
Audio Deep Learning Made Simple - State-of-the-Art Techniques
A Gentle Guide to the world of disruptive deep learning audio applications and architectures. And why we all need to know about Spectrograms, in Plain English.
In Audio, tutorial, Feb 12, 2021
NLP
Foundations of NLP Explained — Bleu Score and WER Metrics
A Gentle Guide to two essential metrics (Bleu Score and Word Error Rate) for NLP models, in Plain English
In NLP, tutorial, May 07, 2021
Foundations of NLP Explained Visually - Beam Search, How It Works
A gentle guide to how Beam Search enhances predictions, in plain English
In NLP, tutorial, Apr 01, 2021
Optimizer
Neural Network Optimizers Made Simple - Core algorithms and why they are needed
A Gentle Guide to fundamental techniques used by gradient descent optimizers like SGD, Momentum, RMSProp, Adam, and others, in plain English.
In Optimizer, tutorial, Apr 07, 2021
GeoLocation
Leveraging GeoLocation Data with Machine Learning - Essential Techniques
A Gentle Guide to Feature Engineering and Visualization with Geolocation Data, in Plain English
In GeoLocation, tutorial, Apr 11, 2021
Vision
Image Captions with Attention in Tensorflow, Step-by-step
An end-to-end example using Encoder-Decoder with Attention in Keras and Tensorflow 2.0, in Plain English
In Vision, tutorial, Apr 27, 2021
Image Captions with Deep Learning - State-of-the-Art Architectures
A Gentle Guide to Image Feature Encoders, Sequence Decoders, Attention, and Multimodal Architectures, in Plain English
In Vision, tutorial, Apr 20, 2021
Neural
Enterprise ML - Why putting your model in production takes longer than building it
A Gentle Guide to Enterprise, in Plain English
In Neural, tutorial, Jun 28, 2021
Batch Norm Explained Visually - Why does it work?
A Gentle Guide to the reasons for the Batch Norm layer's success in making training converge faster, in Plain English
In Neural, tutorial, May 27, 2021
Differential and Adaptive Learning Rates - Neural Network Optimizers and Schedulers demystified
A Gentle Guide to boosting model training and hyperparameter tuning with Optimizers and Schedulers, in Plain English
In Neural, tutorial, May 22, 2021
Batch Norm Explained Visually — How it works, and why neural networks need it
A Gentle Guide to an all-important Deep Learning layer, in Plain English
In Neural, tutorial, May 10, 2021
Enterprise
Enterprise ML - Why building and training a "real-world" model is hard
A Gentle Guide to the lifecycle of a Machine Learning project in the Enterprise, the roles involved and the challenges of building models, in Plain English
In Enterprise, Jun 16, 2021
Featured
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Enterprise ML - Why putting your model in production takes longer than building it
In Neural, tutorial, -
Enterprise ML - Why building and training a "real-world" model is hard
In Enterprise, -
Transformers Explained Visually - Not just how, but Why they work so well
In Transformers, tutorial, -
Differential and Adaptive Learning Rates - Neural Network Optimizers and Schedulers demystified
In Neural, tutorial, -
Foundations of NLP Explained — Bleu Score and WER Metrics
In NLP, tutorial, -
Image Captions with Attention in Tensorflow, Step-by-step
In Vision, tutorial, -
Leveraging GeoLocation Data with Machine Learning - Essential Techniques
In GeoLocation, tutorial, -
Foundations of NLP Explained Visually - Beam Search, How It Works
In NLP, tutorial, -
Audio Deep Learning Made Simple - Automatic Speech Recognition (ASR), How it Works
In Audio, tutorial, -
Audio Deep Learning Made Simple - Sound Classification, Step-by-Step
In Audio, tutorial, -
Audio Deep Learning Made Simple - Why Mel Spectrograms perform better
In Audio, tutorial, -
Audio Deep Learning Made Simple - State-of-the-Art Techniques
In Audio, tutorial, -
Transformers Explained Visually - How it works, step-by-step
In Transformers, tutorial, -
Transformers Explained Visually - Overview of Functionality
In Transformers, tutorial, -
Reinforcement Learning Made Simple - Intro to Basic Concepts and Terminology
In Reinforcement Learning, tutorial,