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technics list
Features Transform case1
Features Transform case2
Outline
Kernel Tricks
Kernel SVM
mnist example with kernel trick
fashion-mnist
AutoML
Statistical Classification
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Cross Entropy
Mnist Logistic Regression
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Naive Bayes Classifier
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Decision Trees
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Heart Disease Tree Classifier
Linear Regression
Linear Regression: Model Imperfection and Steps to Implement Regression
Polynomial regression
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AI Program
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R2 Score
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\({L}^{2}\)
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Polynomial Fit with LASSO Regularization
outliers
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RANSAC
Polynomial Fit with RANSAC
Weighted Least Squares
Non-Linear Least Squares (NLLS)
ElasticNet
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kernel regression
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Kernel Regression
boston house Kernel Regression
Polynomial Regression
Polynomial Regression
Spline Interpolation
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Regression - Decision Tree
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Variance and Bias Trade-off
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HDBSCAN
HDBSCAN Demo
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pca
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svd (pca)
Gene PCA DEMO LAB
PCA DEMO FACES
PCA Brest Cancer
non Linear PCA
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Dimensionality Reduction - Kernel PCA
MDS
MultiDimensional Scaling (MDS)
Manifold Learning
isoMap
Manifold Learning - IsoMap
Spectral Clustering
TSNE
t-SNE Demo
Entropy
Umap
parametric Embedding
umap demo
manifold concepts demo
Manifold Learning - multi model compare
Anomaly detection
zscore
Mahalanobis
Time Series
Local Outlier Factor
Local Outlier Factor
LOF Exercise
Isolation forest
Anomaly Detection - Isolation Forest
Isolation Forest - Exercise
text Analysis
text opts
AI Computer Vision
Labs
Convolution in Deep Learning
Fully Connected Drawbacks
CNN for Frequency Estimation Problem
Convolution for Frequency Estimation
2D Convolution
Layers in Convolutional Neural Networks
Pooling in Convolutional Neural Networks
Batch Normalization
demo batch norm
Common Filters for 2D Convolution
Common Filters for 2D Convolution
Receptive Field (RF)
Calc RF
Encode-Decode Networks
skip connections
cifar10-2d-convolution
Image Classification Fashion MNIST
studentTeacherDemo
pytorch for CV
pytorch layers
custom nn
micro macro
TorchVision
torchvision.transforms
Augmentation
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Cut Effects
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Regularized Training
compare
darknet53
AlexNet
vgg
googleNet
Inception Modules
resnet
ResNet Model
yolo
minirocket
lab simple minirocket demo
Pre-Defined Models
pytorch Inference
sota - state-of-the-art
zoo(s)
Pre Trained Computer Vision Models
Transfer Learning
compare methods
Fine-Tuning
Freeze Layers
Transfer Learning of resnet
Transfer overfit
lab reduce demo
transformers
lab transform basic
adaptation
visualize and debug
Object Location
pre-trained model for object localization
Localization
Object Localization
Detection
Transforms v2: End-to-end object detection/segmentation example
Common Object Detector Architecture
Non Maximum Suppression (NMS)
Mean Average Precision (mAP)
WorkShop - Object Detection with Yolov8
label example
yoloWRKSHP box formats
segmentation workshop
intro
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UNET
the task
Repository
Open issue
.md
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mnist example with kernel trick
mnist example with kernel trick
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