Resources

I'm often asked for resources on how to break into tech (data science and product management) as well as for tips on entrepreneurship. So I've compiled some resources that I've found helpful! 

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Data Science & Machine Learning

1. Practical Statistics for Data Scientists. Concise book that touches on the most common statistical techniques and concepts that data scientists use.
   
2. Data Science Cheat Sheet. Great cheat sheet for all things data science.
3. Practical Statistics for Data Scientists. Concise book that touches on the most common statistical techniques and concepts that data scientists use.
4. W3Schools SQL Tutorial. No frills (and free) guide to learning SQL.
   
5. Data Mining for Business Intelligence. Very good intro to data science techniques, especially for those with a business, finance, management, or strategy background.
6. Chris Albon. Simple website with lots of helpful code snippets of common data science and machine learning tasks in Python.
7. 10 Python File System Methods You Should Know. Helpful file manipulation methods in Python.
8. Lesser Known Python Libraries for Data Science. A useful collection of Python libraries that help with things like fetching files from the web and fuzzy text search.
9. Andrew Ng's Machine Learning Course. My favorite online course for machine learning. It's a great intro.
   
10. Hands-On Machine Learning with Scikit-Learn and TensorFlow. Comprehensive and practical book on machine learning in Python.
11. Deep Learning with Python. This is a great practical intro to deep learning, written by the developer of Keras, Francios Chollet.
12. Stanford Machine Learning Cheat Sheet. Website for Stanford machine learning class that has useful conceptual explanations of supervised learning, unsupervised learning, and deep learning.
13. The Current Best of Universal Word Embeddings and Sentence Embeddings. A blog post on recent advances in word embeddings and the current state of the art methods.
14. The Elements of Statistical Learning. A detailed and thorough book on applied statistics for ML/data science.
    
15. Stanford's CS224d. Stanford's deep learning course for natural language processing (NLP).
    
16. Stanford's CS231. Useful course materials on deep learning for image recognition.
    
17. Learning Math for Machine Learning. A guide to math concepts that are helpful to know if you're interested in machine learning.
    

Product Management

1. HBS Professor Tom Eisenmann's PM Resources. An amazingly thorough repository of helpful resources for those looking to break into product. Some of the links below are cherrypicked from here (I've pulled out the resources that have been most useful to me personally).
2. Business Model Generation. This book offers a powerful conceptual framework for launching new businesses. A classic and a helpful reference to have on hand. ‍‍
3. Just Enough Research. User research is a crucial, yet often under appreciated, piece of the product development process. It's so important for product managers to understand how to incorporate research into their decision making. This book is a quick guide, tailored to the non-research-expert, on how to "do" user research.
4. Good Products Bad Products. A deep dive into the core elements of quality products. Rooted in physical product analysis, but much of the insight is transferrable to software.

Entrepreneurship

1. Venture Deals. Great advice and insight on the fundraising process, with a heavy emphasis on practical knowledge (e.g. what do these terms mean and which terms should I pursue?). Written by the legendary Brad Feld, who is Co-founder of Techstars.
2. The Mom Test. A super quick read that lends a framework for honest insights generation. When you're sussing out a new business idea, you have to be really careful about who you ask for input and HOW you ask for that input, so that you can get to the truth.
3. Y Combinator Library. Repository of Y Combinator resources accumulated over 15 years. Lots of material to sift through, but SUPER helpful stuff.
4. Obviously Awesome. The best book on product positioning I've ever read! 
5. The Innovator's Solution. A crucial book on business strategy, centered around disruption, crafted by one of the best business thinkers of our time (Clay Christensen). The bedrock of disruption theory and a must read.

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