Apeltsin L. Data Science Bookcamp: Ten Python Projects

Manning Publications, 2019. — 247 p.Learn data science with Python by building 10 real-world projects! In Data Science Bookcamp you’ll test and build your knowledge of Python and learn to handle the kind of open-ended problems that professional data scientists work on daily. Downloadable data sets and thoroughly-explained solutions help you lock in what you’ve learned, building your confidence and making you ready for an exciting new data science career.About the TechnologyIn real-world practice, data scientists create innovative solutions to novel open ended problems. Easy to learn and use, the Python language has become the de facto language for data science amongst researchers, developers, and business users. But knowing a few basic algorithms is not enough to tackle a vague and thorny problem. It takes relentless practice at cracking difficult data tasks to achieve mastery in the field. That’s just what this book delivers.
About the book
Data Science Bookcamp is a comprehensive set of challenging projects carefully designed to grow your data science skills from novice to master. Veteran data scientist Leonard Apeltsin sets 10 increasingly difficult exercises that test your abilities against the kind of problems you’d encounter in the real-world. As you solve each challenge, you’ll acquire and expand the data science and Python skills you’ll use as a professional data scientist. Ranging from text processing to machine learning, each project comes complete with a unique downloadable data set and a fully-explained step-by-step solution. Because these projects come from Dr. Apelstin’s vast experience, each solution highlights the most likely failure points along with practical advice for getting past unexpected pitfalls. When you wrap up these 10 awesome exercises, you’ll have a diverse relevant skill set that’s transferable to working in industry.Finding the winning strategy in a card game
Assessing online ad-clicks for significance
Tracking disease outbreaks using news headlines
Predicting scientific trends from paper abstracts
Social circle detection in facebook data
Predicting anomalies in product purchase time series data
Optimizing ad purchases for a planned marketing campaign
Discovering conflicting viewpoints in product tweets using
Sentiment analysis
Creating a balanced sales territory for a sales team
Predicting stock price movements