Workshop 02 | Machine Learning: Zero to Hero Data Preprocessing, which is an integral step in Machine Learning as the quality of data and the useful information that can be derived from it directly affects the ability of our model to learn; therefore, it is extremely important that we preprocess our data before feeding it into our model. We will dive into some core preprocessing techniques using sklearn library and why we need to use it and when. Data Preprocessing is itself another discipline involved in our lives to derive the best in raw data. But focusing on the One - Month program we will be sharing some general methods of Preprocessing which are essential to know before diving into Machine Learning.
Friday, October 2, 2020
3:00 PM β 4:45 PM UTC
Introduction to Data Preprocessing |
Standard Scaling |
MinMAxScaler |
RobustScaler |
Normalizer |
Binarization |
Encoding Categorical Values |
Imputation |
Polynomial Features |
Custom Transformers |
Text Processing & CountVectorizer |
Tfldf vectorizer |
Hashing Vectorizer |
Image Processing using SkImage |
Q/A |
Lenaar Digital
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Softseek International
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HnH Soft Tech Solutions Pvt Ltd
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