Machine Learning Guide
About This Show
This series aims to teach you the high level fundamentals of machine learning from A to Z. I'll teach you the basic intuition, algorithms, and math. We'll discuss languages and frameworks, deep learning, and more. Audio may be an inferior medium to task; but with all our exercise, commute, and chores hours of the day, not having an audio supplementary education would be a missed opportunity. And where your other resources will provide you the machine learning trees, I’ll provide the forest. Additionally, consider me your syllabus. At the end of every episode I’ll provide the best-of-the-best resources curated from around the web for you to learn each episode’s details.
Most Recent Episode
19. Natural Language Processing 2
Natural Language Processing classical/shallow algorithms. ## Episode - Edit distance: Levenshtein distance - Stemming/lemmatization: Porter Stemmer - N-grams, Tokens: regex - Language models ** Machine translation, spelling correction, speech recognition - Classification / Sentiment Analysis: SVM, Naive bayes - Information Extraction (POS, NER): Models: MaxEnt, Hidden Markov Models (HMM), Conditional Random Fields (CRF) - Generative vs Discriminative models ** Generative: HMM, Bayes, LDA ** Discriminative: SVMs, MaxEnt / LogReg, ANNs ** Pros/Cons ** Generative depends on fewer data (NLP tends to be few data) ** MaxEnt vs Naive Bayes: Independence assumption of Bayes, etc ("Hong" "Kong") - Topic Modeling and keyword extraction: Latent Dirichlet Allocation (LDA) ** LDA ~= LSA ~= LSI: Latent diriclet allocation, latent semantic indexing, latent semantic analysis - Search / relevance / document-similarity: Bag-of-words, TF-IDF - Similarity: Jaccard, Cosine, Euclidean ## Resources - Speech and Language Processing (http://amzn.to/2uZaNyg) - Stanford NLP YouTube (https://www.youtube.com/playlist?list=PL6397E4B26D00A269) ** Setup youtube-dl (https://github.com/rg3/youtube-dl) and run `youtube-dl -x --audio-format mp3 https://www.youtube.com/playlist?list=PL6397E4B26D00A269` - NLTK Book (http://www.nltk.org/book)