Embedded Files
You like articles? Me too
Either writing articles to share your knowledge about what you know, or reading to learn something new. They've proven to be useful.
Either writing articles to share your knowledge about what you know, or reading to learn something new. They've proven to be useful.
Below are some of my data science articles.
Below are some of my data science articles.
Unsupervised Learning: Building Score Metrics for Cluster Points
Unsupervised Learning: Building Score Metrics for Cluster Points
Clustering is an unsupervised machine learning technique used for discovering interesting patterns in data. An example would be grouping similar customers based on their behavior, building a spam filter, identifying fraudulent or criminal activity.
Here's what I've learned about Sklearn.resample
Here's what I've learned about Sklearn.resample
Working with imbalanced dataset can be a tough nut to crack for data scientist. One of the ways at which you deal with imbalanced datasets is by resampling with sklearn.resample i.e. upsampling the minority class or downsampling the majority class.
Image Classification Using the Variational Autoencoder
Image Classification Using the Variational Autoencoder
Conventional Image identification using Neural Networks requires Image Labeling. Image Labeling can be a tedious, or more so expensive, activity to do. Imagine running a company that has large datasets of images, and every time we need to build an image identification algorithm for a particular image kind, we need to label the images as ‘instance’ and ‘not instances’. For example, ‘cats’ and ‘not cats’ or ‘dogs’ and ‘not dogs’. The problem is there are many kinds of ‘not instances’.
Ensemble Methods: Comparing Scikit Learn’s Voting Classifier to The Stacking Classifier.
Ensemble Methods: Comparing Scikit Learn’s Voting Classifier to The Stacking Classifier.
Two heads, they say, is better than one. Sometimes in many Machine Learning projects we want to make use of the power of synergy using ensemble methods. The voting and the stacking classifier brings us the benefit of combining 2 or more machine learning models for higher predictive performance.
Using NLP to determine the Sentiments of Lagos-tweets
Using NLP to determine the Sentiments of Lagos-tweets
Everyone talks about Lagos being the city where dreams are fulfilled and all aspirations are graciously met. These thoughts have brought about the former capital being overwhelmingly flooded with its 20 Local Government Areas being currently inhabited by over 16 million people.
How Important is Self Learning in Data Science?
How Important is Self Learning in Data Science?
Learning never really ends in Data Science. Right from the very first day one starts to learn Data Science, till gaining some proficiency and eventually a job in Data Science, learning still continues. As one gets deeper in the art, the kind of questions asked, interests, etc. may change, requiring also a change in the channel/method of learning.
Page updated
Google Sites
Report abuse