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
spectral co-clustering, spectral bi-clustering
(ex) classifier confidence
calibration
cross-validation
metrics
regressions
MNIST, metrics, confusion matrix, precision & recall, ROC, multiple classes, error analysis, multiple labels, multiple outputs
overview, k-means, affinity propagation, mean shift, spectral, hierarchical, dbscan, optics, birch, metrics
intro, random projections, feature agglomeration, dimensional reduction, noise filter, eigenfaces
empirical, shrunk, sparse invariance, robust estimation
user guide, ROC curves, K-fold, LvO, LpO, stratified, shuffled, group-K-fold
training, viz, predictions, CART, gini vs entropy, regularization
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
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
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
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
DNNs
(scikit-and-tensorflow-workbooks)
gradients, activation functions, batch normalization, gradient clipping, model reuse, layer freeze & cache, model zoos, regularization
RNNs
(scikit-and-tensorflow-workbooks)
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
intro
(scikit-and-tensorflow-workbooks)
installation, graphs, gradient descent, momentum, model save-restore, visualization, tensorboard, sharing variables
perceptrons, MLPs, backprop, training,
openAI gym, policies, markov decision processes, q-learning
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
threads, multiprocessing, concurrent, subprocess, sched, queue, _thread, _dummy_thread
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
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
itertools, functools, operators
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
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