Brian Spiering

awesome-dl4nlp. A curated list of awesome Deep Learning (DL) for Natural Language Processing (NLP) resources

awesome-deep-rl. A curated list of awesome Deep Reinforcement Learning resources

nlp-course. An introduction to Natural Language Processing (NLP) course

word2vec-workshop. word2vec workshop - a conceptual introduction and practical application

keras-intro. An Absolute Beginner's Guide to Deep Learning with Keras, a PyBay 2018 talk

rl-course. Applied Reinforcement Learning course

gaussian_mixture_models. Jupyter Notebook

statistical-analysis-of-fMRI-data-book-examples. Coding examples from Statiscal Analysis of fMRI data by F. Gregory Ashby

machine-learning-in-scikit-learn. Introduction to machine learning in scikit-learn

word2vec-talk. Slides and coding demo for word2vec

awesome-raymond-hettinger. A curated list of awesome Raymond Hettinger talks.

py4datascience. Python Fundamentals for Data Science: A PyBay 2019 Workshop

cs486-career-prep. University of San Francisco's CS 486 Special Topic: Career Prep

tensorflow-workshop. A brief hands-on introduction to TensorFlow

PythonDataScienceHandbook. Python Data Science Handbook: full text in Jupyter Notebooks

deep_text_classification. A Gentle Introduction to Text Classification with Deep Learning

nlp-cookbook. Applying NLP to solve business problems

coding-challenges. My solutions to coding challenges

quotes_from_others. A collection of quotes I like

course-directory. Directory of courses I have developed and delivered

programming_study_group. A collection of lessons covering the fundamental programming concepts for technical interviewing

word-embeddings-workshop. Hands-on workshop for word embeddings

teaching_materials. Collection of teaching related documents

ComputationalStatistics. An Introduction to Computational Statistics in Python for Data Institute Conference 2019

streamlit_examples. Examples of Streamlit apps

smart-cards. SmartCards: Automagically make flashcards. Built in a weekend at HackingEDU Hackathon

family_style_chatbot. Group food ordering make easy

quotes_from_me. Collection of quotes by me (possibly)

save-circular-sine-wave-gratings. Exports circular sine wave gratings typically found in categorization research.

pytorch-tutorials. Jupyter Notebook

naive_bayes_classifer_in_python_3_8. Jupyter Notebook

PyDataSIG. PyData Special Interest Group @ SF Python Project Night

nbgrader_utilities_for_canvas. Utilities to automatically run nbgrader and post scores to Canvas LMS

logistic_regression_intro. A brief introduction to logistic regression

knowledge-graph-workshop. 1-day workshop on knowledge graphs (KG): Learn the theory and hands-on coding

naive_bayes_intro. Introduction to Naive Bayes - a Machine Learning Classification Algorithm

scikit-learn-pipeline-intro. A quick introduction to writing more robust machine learning code with scikit-learn's pipelines.

mermaid_examples. Mermaid creates diagrams and visualizations based on a text language similar to Markdown.

llm_examples. Applied examples of large language models (LLM)

how_to_give_a_techical_presentation. Best practices for technical presentations

advent_of_code_2018. Advent of Code 2018 🎄🎁

locality-sensitive-hashing. Approximate Nearest Neighbors with Locality-sensitive Hashing

aima-pseudocode. Pseudocode descriptions of the algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"

fibonacci_sequences. Fibonacci sequences for fun & profit

binary_search_trees. A gentle introduction to Binary Search Trees (BST)

msds689. Course syllabus, notes, projects for USF's MSDS689

problem_solving_in_multiple_programming_paradigms. Tutorial for SF Python Project Night: Solving the same problem in multiple programming paradigms.

doing-bayesian-data-analysis. Exploring John K. Kruschke's Doing Bayesian Data Analysis

DataHack14. Backend code for DataHack14.

python-algorithms. My work exploring the code from Python Algorithms by Magnus Lie Hetland