StdLib
NumPy
Pandas
Statistics
SciPy
Feature Engineering
Machine Learning
Scikit-Image
Natural Language Processing
TensorFlow
PyTorch
Visualization (Matplotlib, Seaborn, ...)
Symbolics (SymPy)
Optimization (Numba, Cython)
Utilities

posix, pwd, spwd, grp, crypt, termios, tty, pty, fcntl, pipes, resource, nis, syslog

msilib, msvcrt, winreg, winsound

os, io, time, argparse, getopt, logging, getpass, curses, platform, error, ctypes

struct, codecs

threads, multiprocessing, concurrent, subprocess, sched, queue, _thread, _dummy_thread

hashlib, hmac, secrets

code, codeop

datetime, calendar, collections, heapq, bisect, array, weakref, types, copy, pprint, reprlib, enum

boolean, comparisons, numerics, iterators, sequences, text sequences, binary sequences, sets, maps, context managers, more

bdb, faulthandler, pdb, profilers, timeit, trace, tracemalloc

martin heinz tutorial

martin heinz tutorial

typing, pydoc, doctest, unittest, 2to3, test

basics, concrete exceptions, warnings, hierarchy

zlib, gzip, bz2, lzma, zipfile, tarfile

csv, configparser, netrc, xdrlib, plistlib

pickle, copyreg, shelve, marshal, dbm, sqlite3

pathlib, os.path, fileinput, stat, filecmp, tempfile, glob, fnmatch, linecache, shutil

turtle, cmd, shlex

itertools, functools, operators

gettext, locale

webbrowser, cgi, cgitb, wegiref, urllib, http, ftplib, poplib, imaplib, nntplib, smtplib, smtpd, telnetlib, uuid, socketserver, http.server, http.cookies, xmlrpc, ipaddress

parser, ast, symtable, symbol, token, keyword, tokenize, tabnanny, pyrlbr, py_compile, compileall, diss, pickletools

html, xml

zipimport, pkgutil, modulefinder, runpy, importlib

audioop, aifc, sunau, wave, chunk, colorsys, imghdr, sndhdr, ossaudiodev

email, json, mailcap, mailbox, mimetypes, base64, binhex, binascii, quopri, uu

asyncio, socket, ssl, select, selectors, asyncore asynchat, signal, mmap

numbers, math, cmath, decimal, fractions, random, statistics

disutils, ensurepip, venv, zipapp

sys, sysconfig, builtins, __main__, warnings, dataclasses, contextlib, abc, atexit, traceback, __future__, gc, inspect, site

optparse, imp

tkinter, more...

datatypes, typecasting, promoting, complex numbers, memory, arrays, indexes, slices, views, fancy indexing, boolean indexing, reshaping, merging, vectorization, math ops, aggregate ops, boolean arrays, conditionals, logic, set ops, matrix ops

arrays, boolean arrays, masking, broadcasting, fancy indexes, sorting, structured data, aggregations, ufuncs, datatypes

TDS article search

series, dataFrames, time series

aggregations, groups, concat/append, hierarchical indexes, merge/join, missing values, pivot tables, time series, vectorized objects

date ranges, merges, save to excel, file compression, histograms, pdfs, cdfs, least squares, timing, display options, pandas 1.0 features

normal distribution, dependent variables, posterior distributions, linear regression, multilevel models

random numbers, distributions, hypothesis testing, kernel density estimation

patsy, categorical variables, linear regression, discrete & logistic regression, poisson distribution, time series

symbolic solutions, directional field graphs, laplace transforms, numerical methods, numerical integration

--NOT WORKING YET--

simpson's rule, multiple integration, scikit-monaco, symbolic/multiprecision quadrature, laplace transforms, fourier transforms

polynomials, splines, multivariates

spectral analysis, fourier transforms, frequency-domain filters, windowing, spectrograms, convolutions, FIRs, IIRs

sparse matrices, sparse linear algebra, eigenvalue problems, graphs & networks

setup, tips, caching, regression target transforms

univariate, multivariate, nearest-neighbor, marking imputed values

iris, digits, cal housing, labeled faces, 20 newsgroups, (more)

one-hot encoding, word counts, tf-idf, linear-to-polynomial, missing data, pipelines

CSV, HDF5, h5py, pytables, hdfstore, JSON, serialization, pickle issues

mean removal, variance scaling, sparse scaling, outlier scaling, distribution maps, normalization, category coding, binning, binarization, polynomial features.

bag of words, sparsity, vectorizers, stop words, tf-idf, decoding, applications, limits, the hashing trick, out-of-core ops

spectral co-clustering, spectral bi-clustering

MNIST, metrics, confusion matrix, precision & recall, ROC, multiple classes, error analysis, multiple labels, multiple outputs

label propagation

overview, k-means, affinity propagation, mean shift, spectral, hierarchical, dbscan, optics, birch, metrics

intro, random projections, feature agglomeration, dimensional reduction, noise filter, eigenfaces

pipeline, feature union

empirical, shrunk, sparse invariance, robust estimation

PLS, CCA

user guide, ROC curves, K-fold, LvO, LpO, stratified, shuffled, group-K-fold

training, viz, predictions, CART, gini vs entropy, regularization

classification, regression, multiple outputs, complexity, tips, algos (ID3, C4.5, C5.0, CART), math, minimal cost-complexity pruning

histograms, spherical KDEs, custom estimators

validation, linear algebra, arrays, random sampling, graphs, testing, multiclass/multilabel, helpers, hashes, warnings, exceptions

curse of dimensionality, projections, manifolds, PCA, explained variance, choosing dimensions, PCA for compression, incremental PCA, randomized PCA, kernel PCA, selecting a kernel, LLE, MDS, isomap, t-SNE, LDA

dimensionality reduction, LDA, math, shrinkage, estimators

cosine similarity, kernels (linear, polynomial, sigmoid, RBF, laplacian, chisqd)

low-variance features, univariate selection, recursive elimination, selecting from a model, pipeline ops

expectation maximization (EM), confidence ellipsoids, bayes info criterion & n_clusters, covariance constraints (spherical, diagonal, tied, full), variational bayes (extension of EM)

regressions, classifiers, kernels

classification, regression, sparse data, complexity, stopping, tips, implementation

user guide, grid search, random parameters, tips, brute force alternatives

noestrem method, std kernels

user guide, OLS, ridge regression, lasso, elastic net, LARS, OMP, bayes, ARD, passive-aggressive algos, robustness, ransac vs theil-sen vs huber, polynomial regression

hello, MDS, non-linear embeddings, tradeoffs, isomap on faces

projections, PCA, principal components, MDS, locally linear embeddings (LLE), modified LLE, hessian eigenmaps, spectral embeddings, LTSA, t-SNE, isomap

PCA, incremental PCA, kernel PCA, sparse PCA, dictionary learning, factor analysis, ICA, NNMF, LDA

label formats, OvR, OvO, ECCs, multiple outputs, classifier chains, regressor chains

definition, as a classifier, as a regressor, regularization, loss functions, complexity, math, tips, warm_start

gaussian, multinomial, complement, bernoulli, out-of-core

unsupervised, KD trees, Ball trees, regressions, nearest centroids, NCA

definitions, methods, novelty detection, outlier detection, elliptic envelope, iso forest, local outlier factor, novelties with LOF

see list of kernels

python vs cython vs c, code profiling, memory profiling, cython tips, profiling compiled extensions, joblib.Parallel, warm_start

parameters, bernoulli RBM, stochastic max likelihood learning

classification, regression, density estimates, novelty detection, complexity, tips, kernel functions, implementation

classification (linear), classification (nonlinear), polynomial features, the kernel trick, similarity functions, gaussian RBF kernels, regression

validation curves, learning curves

LI thresholds, max trees

contours, convex hulls, canny edge detectors, matching cubes, ridge ops, active contour model, shapes, hough transforms, skeletonize, polygon ops, edges,

RGB to grayscale, RGB to HSV, histogram matching, histogram equalization, cell stain color separation, grayscale filters & RGB images, regional maxima, gamma & log contract adjustments, tinting

DAISY, template matching, corner detection, filling holes, finding peaks, CENSURE, gabor filters, ORB, shape indexes, sliding window histograms, texture classification

hysteresis thresholds, image deconvolution, mean filters, unsharp masks, inpainting, entropy, denoising, wavelets, phase unwrapping, attribute operators

crash course, image datatypes, image adjustments, video files, basic tutorials

cascade classifiers, edge- vs region-based segmentation, image compression, rank filters

normalized cut, RAGs, thresholding, watershedding, local maxima, image region labels, flood fills, morphological snakes

swirl, image pyramids, rescale, resize, downscale, piecewise affine transforms, structural similarities, phase correlation, polar, log-polar transforms, line model estimation, radon transforms

similarity queries, text summaries, distance metrics, LDA, Annoy, PDLN, doc2vec, word mover, fasttext

data cleanup, bag of words, classifier fit, metrics, feature pareto, tf-idf, semantic meanings, CNN

tokens, POS tags, dependency parsing, lemmas, sentence boundaries, named entities, similarity, text classification, rule-based matches, training, serialization

tokenizization, stopwords, GloVe embeddings,

gradients, activation functions, batch normalization, gradient clipping, model reuse, layer freeze & cache, model zoos, regularization

intro, sequences, unrolling, simplification, training, deep RNNs, LSTMs, GRU cells, NLP basics

intro, stacked AEs, tying weights, reconstructions

layers, filters, map stacking, padding & pooling, architectures

installation, graphs, gradient descent, momentum, model save-restore, visualization, tensorboard, sharing variables

perceptrons, MLPs, backprop, training,

openAI gym, policies, markov decision processes, q-learning

tensors, numpy arrays, cuda, autograd, gradients, neural net design, loss functions, backprop, weight updates, training, CNN definition, testing, GPU training, parallelism

LOTs of plot types

square vs rectangular, eigenvalues, nonlinear equations, univariate equations

symbols, numbers, rationals, constants, functions, expressions, simplification, expansion, factor, collect, combine, apart, together, cancel, substitutions, evaluations, calculus, sums, products, equations, linear algebra

installation, will it work?, nopython, performance, under the hood, @decorators, groups

numba, numba.vectorize, cython, tips & tricks, cython & C