dlab-berkeley / Python-Deep-Learning-Legacy
D-Lab's 6 hour introduction to deep learning in Python. Learn how to create and train neural networks using Tensorflow and Keras.
☆17Updated 2 years ago
Alternatives and similar repositories for Python-Deep-Learning-Legacy:
Users that are interested in Python-Deep-Learning-Legacy are comparing it to the libraries listed below
- D-Lab's 6 hour introduction to machine learning in Python. Learn how to perform classification, regression, clustering, and do model sele…☆82Updated 4 months ago
- D-Lab's 3 hour introduction to data visualization with Python. Learn how to create histograms, bar plots, box plots, scatter plots, compo…☆56Updated 2 years ago
- D-Lab's 12 hour introduction to Python. Learn how to create variables and functions, use control flow structures, use libraries, import d…☆168Updated 2 years ago
- D-Lab's 3 hour introduction to basic Bash commands and using version control with Git and Github.☆133Updated 10 months ago
- A starting point for discovering the wonderful world of Git, GitHub, and Git Annex (Assistant)☆75Updated 5 years ago
- D-Lab's 3 hour introduction to data wrangling in Python. Learn how to import and manipulate dataframes using pandas in Python.☆52Updated 2 years ago
- Public code & notebooks accompanying our blog posts & YouTube tutorials (https://www.youtube.com/c/PyMCLabs)☆24Updated 2 months ago
- We use Python to get intuition on complex concepts, empirically test theoretical proofs, or build algorithms from scratch☆21Updated 3 years ago
- D-Lab's 6-part, 12-hour introduction to Python. Learn how to create variables, use methods and functions, work with if-statements and for…☆44Updated 4 months ago
- D-Lab's 12 hour introduction to R Fundamentals. Learn how to create variables and functions, manipulate data frames, make visualizations,…☆140Updated 2 years ago
- Workshop (6 hours): preprocessing, cross-validation, lasso, decision trees, random forest, xgboost, superlearner ensembles☆190Updated 3 years ago
- D-Lab's 4 part, 8 hour introduction to R Fundamentals. Learn how to create variables and functions, manipulate data frames, make visualiz…☆35Updated last month
- D-Lab's 2 hour introduction to web scraping in Python. Learn how to scrape HTML/CSS data from websites using Requests and Beautiful Soup.☆11Updated 10 months ago
- Workshop (6 hours): Deep learning in R using Keras. Building & training deep nets, image classification, transfer learning, text analysis…☆124Updated 10 months ago
- D-Lab's 3 hour introduction to data visualization with R. Learn how to create histograms, bar plots, box plots, scatter plots, compound f…☆28Updated last year
- Regular expression concepts with code examples☆12Updated 3 years ago
- Interactive flashcards and quizzes, as well as additional tutorials, animations, and code, for "Foundations of Data Science with Python" …☆22Updated 2 months ago
- Data visualization in Python with Matplotlib & Seaborn☆43Updated 2 years ago
- Website: Data Umbrella & PyMC open source sessions☆26Updated 8 months ago
- Explorations of survival analysis in Python☆51Updated 2 years ago
- Present your data as an effective and compelling story☆105Updated 5 years ago
- Beginner's introduction to the pandas library for data manipulation☆25Updated 3 years ago
- Content from the University of British Columbia's Master of Data Science course DSCI 511.☆86Updated last year
- This repository contains the codes for the Python tutorials on statology.org☆27Updated 4 years ago
- ☆10Updated 7 years ago
- Scientific Computing in Python, a practical and ultimate tutorials☆13Updated last year
- Python Implementation of multiple unsupervised segmentation models and evaluating them through multiple evaluation metrics☆10Updated 3 years ago
- Hosting the scikit-learn blog.☆16Updated this week
- An end-to-end tutorial to forecast the M5 dataset using feature engineering pipelines and gradient boosting.☆16Updated 2 years ago
- Library for doing both symbolic and numeric calculations for linear Structural Causal Models (SCM)☆14Updated 9 months ago