Random search in Machine Learning
Machine learning(ML) has become one of the hot fields of study and job markets. Day to day we see an increase in demand for people who can build ML models as per user requirements.
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DataScience
datascience
Characteristics of an Ideal ML Model: How to Choose & Why
There are many characteristics of an ideal ML model. The most crucial factor is that the model accurately predicts the target variable. In this blog post, we will discuss how to choose a machine learning model and why each type of model might be helpful in different situations.
datascience
Bias vs Variance: Understanding the difference
The bias-variance tradeoff is crucial in data science when creating a machine learning model. Underfitting is seen when a model exhibits high bias. Overfitting is seen in the model when it shows high variance. Therefore, it's essential to balance these two and reduce errors.
datascience
Data Scientist vs Data Analyst: Understanding the Differences
Are you looking to become a data science expert but don't know how you can distinguish yourself from the rest of the pack? Today, many data-driven companies are looking to hire either data scientists or data analysts. There are many data scientist jobs and data analyst jobs.
datascience
What is the Manhattan Distance in Machine Learning?
In this article, we will discuss Manhattan distance and why it is used for higher dimensionality data.