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.
250+ End-to-End Data Science Projects with Source Code
WIRED Brand Lab, How Data Science is Revolutionizing the Mining Industry
Highlight, take notes, and search in the book
R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
Unlock the Power of Machine Learning in Data Science & AI
Customize models in Bedrock with your own data using fine-tuning and continued pre-training
Fine-Tuning LLaMA 2: A Step-by-Step Guide to Customizing the Large Language Model
RAG vs Finetuning — Which Is the Best Tool to Boost Your LLM Application?, by Heiko Hotz
End To End Data Science Playlist- Get Prepared With Industry Ready Projects
Quantitative Analysis: Definition, Importance + Types
Fine-tuning Neural Network Hyperparameters: Best Practices
