This is a data science project practice book. It was initially written for my Big Data course to help students to run a quick data analytical project and to understand 1. the data analytical process, the typical tasks and the methods, techniques and the algorithms need to accomplish these tasks. During convid19, the unicersity has adopted on-line teaching. So the students can not access to the university labs and HPC facilities. Gaining an experience of doing a data science project becomes individual students self-learning in isolation. This book aimed to help them to read through it and follow instructions to complete the sample propject by themslef. However, it is required by many other students who want to know about data analytics, machine learning and particularly practical issues, to gain experience and confidence of doing data analysis. So it is aimed for beginners and have no much knowledge of data Science. the format for this book is bookdown::gitbook.
Underfitting vs. Overfitting
Underfitting and Overfitting - Coding Ninjas
overfitting - Relation between underfitting vs high bias and
Chapter 9 Titiannic Prediction with Random Forest
3.11. Model Selection, Underfitting and Overfitting — Dive into
12.4 Further Analysis Do A Data Science Project in 10 Days
What is underfitting and overfitting of the ML model, and how can
10.2 General Cross Validation Methods
Summary Do A Data Science Project in 10 Days
Overfitting and underfitting in machine learning
Model Validation: Problem Areas and Solutions - Overfitting and
Overfitting and Underfitting With Machine Learning Algorithms
2.2 Downlaod and Install R and RStudio
machine learning - What do Under fitting and Over fitting
12.3 Model Interpretation Do A Data Science Project in 10 Days
