-
Updated
Feb 28, 2022
#
svm
Here are 2,279 public repositories matching this topic...
100 Days of ML Coding
python
machine-learning
tutorial
deep-learning
svm
linear-regression
scikit-learn
linear-algebra
machine-learning-algorithms
naive-bayes-classifier
logistic-regression
implementation
support-vector-machines
100-days-of-code-log
100daysofcode
infographics
siraj-raval
siraj-raval-challenge
AiLearning:数据分析+机器学习实战+线性代数+PyTorch+NLTK+TF2
python
nlp
svm
scikit-learn
sklearn
regression
logistic
dnn
lstm
pca
rnn
deeplearning
kmeans
adaboost
apriori
fp-growth
svd
naivebayes
mahchine-leaning
recommendedsystem
-
Updated
Mar 19, 2022 - Python
python
machine-learning
svm
regression
logistic
python3
adaboost
smo
knn
decision-tree
navie-bayes-algorithm
adaboost-algorithm
-
Updated
Jul 7, 2021 - Python
Python code for common Machine Learning Algorithms
random-forest
svm
linear-regression
naive-bayes-classifier
pca
logistic-regression
decision-trees
lda
polynomial-regression
kmeans-clustering
hierarchical-clustering
svr
knn-classification
xgboost-algorithm
-
Updated
Jan 17, 2022 - Jupyter Notebook
Documents, papers and codes related to Natural Language Processing, including Topic Model, Word Embedding, Named Entity Recognition, Text Classificatin, Text Generation, Text Similarity, Machine Translation),etc. All codes are implemented intensorflow 2.0.
tensorflow
svm
word2vec
crf
keras
similarity
classification
attention
gensim
lda
fasttext
ner
embedding
bert
elmo
-
Updated
Jul 5, 2021 - Python
Vehicle detection using machine learning and computer vision techniques for Udacity's Self-Driving Car Engineer Nanodegree.
machine-learning
udacity
computer-vision
svm
self-driving-car
hog-features
sliding-windows
svm-classifier
-
Updated
Oct 31, 2017 - Jupyter Notebook
The Operator Splitting QP Solver
machine-learning
control
optimization
svm
solver
lasso
portfolio-optimization
numerical-optimization
quadratic-programming
convex-optimization
model-predictive-control
-
Updated
Apr 7, 2022 - C++
Implementation of hyperparameter optimization/tuning methods for machine learning & deep learning models (easy&clear)
machine-learning
deep-learning
random-forest
optimization
svm
genetic-algorithm
machine-learning-algorithms
hyperparameter-optimization
artificial-neural-networks
grid-search
tuning-parameters
knn
bayesian-optimization
hyperparameter-tuning
random-search
particle-swarm-optimization
hpo
python-examples
python-samples
hyperband
-
Updated
Apr 4, 2022 - Jupyter Notebook
利用pytorch实现图像分类的一个完整的代码,训练,预测,TTA,模型融合,模型部署,cnn提取特征,svm或者随机森林等进行分类,模型蒸馏,一个完整的代码
flask
deployment
random-forest
svm
cnn
pytorch
image-classification
densenet
resnet
knn
knowledge-distillation
resnext
label-smoothing
-
Updated
Nov 26, 2021 - Jupyter Notebook
Java Statistical Analysis Tool, a Java library for Machine Learning
-
Updated
May 6, 2021 - Java
Curso de Introducción a Machine Learning con Python
-
Updated
Feb 11, 2022 - Jupyter Notebook
-
Updated
Feb 5, 2020 - Python
JasonShin
commented
Apr 8, 2019
-
I'm submitting a ...
[/] enhancement -
Summary
As a result of upgrading the Tensorflow version to 0.15.1, we should refactor all thedataSycn
witharraySync
. This will greatly improve the overall readability of the code.
good first issue
Good for newcomers
Created vehicle detection pipeline with two approaches: (1) deep neural networks (YOLO framework) and (2) support vector machines ( OpenCV + HOG).
-
Updated
Mar 28, 2018 - Python
Open
如何根据图表分析得出app启动的时间?
5
TatamiHermit
commented
Nov 15, 2019
你好,根据我个人理解,app启动时间的测试,默认的黑盒标准一般是从click event触发开始。
请教一下根据report中的各类图表,首先要获取到精确的click event的时间戳t1,然后获取到界面加载完成的t2,这样就可以得到Δt
我这边打开Android的轨迹,这样点击时就会有一个圆点,可以用于辅助识别。
根据你的设计理念,如何根据图表分析得出app启动的时间呢?
谢谢。
good first issue
Good for newcomers
Regression, Scrapers, and Visualization
visualization
sentiment-analysis
svm
linear-regression
prediction
stocks
stock-prices
hacktoberfest
stock-analysis
nvda
hacktoberfest2020
-
Updated
Oct 10, 2021 - Jupyter Notebook
Simple machine learning library / 簡單易用的機器學習套件
machine-learning
neural-network
svm
linear-regression
regression
classification
logistic-regression
perceptron
decision-trees
support-vector-machines
-
Updated
Jan 7, 2022 - Python
Ruby language bindings for LIBSVM
ruby
machine-learning
svm
ml
ruby-bindings
libsvm
svm-training
svm-learning
svm-classifier
rubyml
ruby-language-bindings
-
Updated
Sep 4, 2020 - C++
도서 "핸즈온 머신러닝"의 예제와 연습문제를 담은 주피터 노트북입니다.
python
machine-learning
deep-neural-networks
reinforcement-learning
deep-learning
neural-network
random-forest
tensorflow
svm
scikit-learn
recurrent-neural-networks
xgboost
autoencoder
ensemble-learning
gradient-boosting
-
Updated
Mar 4, 2020 - Jupyter Notebook
Open Source Landmarking Library
-
Updated
Aug 7, 2019 - Jupyter Notebook
Pytorch、Scikit-learn实现多种分类方法,包括逻辑回归(Logistic Regression)、多层感知机(MLP)、支持向量机(SVM)、K近邻(KNN)、CNN、RNN,极简代码适合新手小白入门,附英文实验报告(ACM模板)
machine-learning
deep-learning
svm
scikit-learn
cnn
python3
pytorch
mnist
rnn
mnist-classification
logistic-regression
mlp
knn
-
Updated
Oct 16, 2020 - Python
SimpleSvmHook is a research purpose hypervisor for Windows on AMD processors.
-
Updated
Feb 18, 2021 - C++
ML based projects such as Spam Classification, Time Series Analysis, Text Classification using Random Forest, Deep Learning, Bayesian, Xgboost in Python
nlp
docker
machine-learning
deep-learning
random-forest
text-classification
tensorflow
svm
word2vec
geolocation
keras
gensim
tensorboard
ab-testing
spam-classification
lstm-neural-networks
imbalanced-data
kdtree
timeseries-analysis
mlflow
-
Updated
Dec 15, 2020
A minimalistic educational hypervisor for Windows on AMD processors.
-
Updated
Aug 16, 2020 - C++
Improve this page
Add a description, image, and links to the svm topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the svm topic, visit your repo's landing page and select "manage topics."
Hi I would like to propose a better implementation for 'test_indices':
We can remove the unneeded np.array casting:
Cleaner/New:
test_indices = list(set(range(len(texts))) - set(train_indices))
Old:
test_indices = np.array(list(set(range(len(texts))) - set(train_indices)))