Bojan Tunguz, a senior systems software engineer at NVIDIA, shared a photo of his book collection on coding, data science, and machine learning on Twitter. The tweet went viral, eliciting numerous responses from the data science and machine learning communities. This collection will get you close to 98 percent – 99 percent of all the necessary core skills to be a good data scientist, he said.
Bojan’s list includes the following:
- Approaching almost any machine learning problem – Abhishek Thakur
- Feature engineering for machine learning – Zheng and Cesari
- Hands-on unsupervised learning using Python – Ankur A. Patel
- Deep learning with Pytorch – Eli Stevens, Luca Antiga, Thomas Viehmann
- Introducing Python – Lubanovic
- Machine learning using TensorFlow cookbook – Alexia Audevart, Konrad Banachewicz, and Luca Massaron
- Natural language processing with transformers – Lewis Tunstall, Leandro von Werra, Thomas Wolf
- Hands-on gradient boosting with XGboost and Scikit – learn – Corey Wade
- Deep learning with python – François Chollet
- Effective Pandas – Matt Harrison
- Machine Learning using Pytorch and scikit – learn
While Bojan’s collection included the most important books on coding, data science, and machine learning, we discovered a few quote tweets mentioning the important books he did not include, like:
- Deep learning for coders with Fastai and Pytorch – Jeremy Howard and Sylvain Gugger
- Deep learning – Ian Goodfellow
- Hands-on machine learning with scikit- learn, Keras and Tensorflow – Geron Aurelien
- Pattern recognition and machine learning – Bishop
Meanwhile, Alex Engler, a research fellow in Governance Studies at The Brookings Institution, believes the list is lacking in books on data collection (tools or theory), SQL, data visualization or communication, experiments, causal inference, and domain knowledge.
In his response, the AI digator emphasized the data science community’s strong bias against the coding language R. Meanwhile, Leon Palafox, Grupo Salinas’ director of artificial intelligence, stated that the collection lacks books on theory.
Bojan Tunguz’s tweet is part of a growing trend on social media in which subject matter experts share their library of books on data science, artificial intelligence, and machine learning.
This trend is not limited to books, but to all types of resources that aspirants can use to gain a thorough understanding of machine learning, data science, and artificial intelligence.
Meanwhile, the trend persisted on Linkedin as well.
