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Apparel Recommendation Engine Workshop
Build a weighted Nearest neighbor model using Visual, Text, Brand and Color
Build a weighted Nearest neighbor model using Visual, Text, Brand and Color
Instructor:
Applied AI Course
Duration:
6 mins
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A/B testing:
Text based product similarity
1.1
Converting text to an n-D vector: bag of words
14 min
1.2
Code for bag of words based product similarity
26 min
1.3
TF-IDF: featurizing text based on word-importance
17 min
1.4
Code for TF-IDF based product similarity
10 min
1.5
Code for IDF based product similarity
9 min
Text Semantics based product similarity
2.1
Word2Vec: featurizing text based on semantic similarity
19 min
2.2
Code for Average Word2Vec product similarity
15 min
2.3
TF-IDF weighted Word2Vec
9 min
2.4
Code for IDF weighted Word2Vec product similarity
6 min
2.5
Weighted similarity using brand and color
9 min
2.6
Code for weighted similarity
7 min
2.7
Building a real world solution
5 min
Deep learning based visual product similarity
3.1
ConvNets: How to featurize an image: edges, shapes, parts
11 min
3.2
Using Keras + Tensorflow to extract features
8 min
3.3
Visual similarity based product similarity
6 min
How do we measure the goodness of our solutions?
4.1
A/B testing:
7 min
Exercise
5.1
Build a weighted Nearest neighbor model using Visual, Text, Brand and Color
6 min
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