- Talk: Learning to Type by Liam Atkinson at the ml4p.org conference in 2018 [deadlink]
- Awesome ML on Source Code
- Machine Learning on Go Code
- ML on Source Code
- Introducing Experiments, an ongoing research effort from GitHub
- C# or Java? TypeScript or JavaScript? Machine learning based classification of programming languages
- Introducing the CodeSearchNet challenge
- Towards Natural Language Semantic Code Search
- Semantic Search
- Sequence-to-sequence
- tree-based LSTMs
- gated-graph networks
- Fine-tuning Deep Learning models in Keras
- BLEU Score
- Universal Sentence Encoder | Tensorflow Hub
- Neural language model | fast.ai
- AWD LSTMs | cyclical learning rates | Universal Language Model Fine-tuning for Text Classification
- A python tool for evaluating the quality of sentence embeddings
- Cosine Proximity Loss | Efficient Natural Language Response Suggestion for Smart Reply
- open-source end-to-end tutorial
- Code Search implemented in Kubeflow | kubeflow
- Live demo of Semantic Code Search | Experiments site
- ML for Detecting Code Bugs
- Machine Learning on Source Code
- ML on Code devroom at FOSDEM
- The Open Source Show: Machine Learning on Code by Rob Caron, Lacey Butler, Allison Cordle
- Machine Learning for Programming - conference held in 2018 in Oxford, UK
- A Transformer-based Approach for Source Code Summarization
- Text generation models in action - code autocompletion:
- TabNine
- https://github.com/Quantum-Game/quantum-tensors | https://transformer.huggingface.co/doc/gpt2-large (just not Markov Model, but some LSTM or maybe even Transformer)
- TransCoder: An AI from Facebook that uses seq2seq attention model composed of encoder and decoder with transformer architecture to translate code from one programming language to another: Paper | Press release
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