Solving real world problems with data science concepts is so exciting and it yields so fun.
A famous dialogue you could listen from the data science people. It could be true if we add it’s so challenging at the end of the dialogue. The foremost challenge starts from categorising the problem itself. The first level of categorising could be whether supervised or unsupervised learning. The next level is what kind of algorithms to get start with whether to start with classification algorithms or with clustering algorithms?
As we have covered the first level of categorising supervised and unsupervised learning in our previous post, now we would like to address the key differences between classification and clustering algorithms. First of all, it’s better to know the differences between classification and prediction before knowing the difference between classification and clustering.
Read complete post: Classification and Clustering Algorithms