Data Cleaning is one of the important steps in EDA. Data cleaning can be done in many ways. One of them is handling missing values. Let’s learn about how to handle missing values in a dataset.
Data Cleaning is one of the important steps in EDA. Data cleaning can be done in many ways. One of them is handling missing values.
Let’s learn about how to handle missing values in a dataset.
Different types of missing values:
This "Deep Learning vs Machine Learning vs AI vs Data Science" video talks about the differences and relationship between Artificial Intelligence, Machine Learning, Deep Learning, and Data Science.
Most popular Data Science and Machine Learning courses — August 2020. This list was last updated in August 2020 — and will be updated regularly so as to keep it relevant
A couple of days ago I started thinking if I had to start learning machine learning and data science all over again where would I start?
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Artificial Intelligence (AI) vs Machine Learning vs Deep Learning vs Data Science: Artificial intelligence is a field where set of techniques are used to make computers as smart as humans. Machine learning is a sub domain of artificial intelligence where set of statistical and neural network based algorithms are used for training a computer in doing a smart task. Deep learning is all about neural networks. Deep learning is considered to be a sub field of machine learning. Pytorch and Tensorflow are two popular frameworks that can be used in doing deep learning.