{ "item_title" : "Data Science Bookcamp", "item_author" : [" Leonard Apeltsin "], "item_description" : "Learn data science with Python by building five real-world projects Experiment with card game predictions, tracking disease outbreaks, and more, as you build a flexible and intuitive understanding of data science. In Data Science Bookcamp you will learn: Techniques for computing and plotting probabilitiesStatistical analysis using ScipyHow to organize datasets with clustering algorithmsHow to visualize complex multi-variable datasetsHow to train a decision tree machine learning algorithm In Data Science Bookcamp you'll test and build your knowledge of Python with the kind of open-ended problems that professional data scientists work on every day. 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. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technologyA data science project has a lot of moving parts, and it takes practice and skill to get all the code, algorithms, datasets, formats, and visualizations working together harmoniously. This unique book guides you through five realistic projects, including tracking disease outbreaks from news headlines, analyzing social networks, and finding relevant patterns in ad click data. About the bookData Science Bookcamp doesn't stop with surface-level theory and toy examples. As you work through each project, you'll learn how to troubleshoot common problems like missing data, messy data, and algorithms that don't quite fit the model you're building. You'll appreciate the detailed setup instructions and the fully explained solutions that highlight common failure points. In the end, you'll be confident in your skills because you can see the results. What's inside Web scrapingOrganize datasets with clustering algorithmsVisualize complex multi-variable datasetsTrain a decision tree machine learning algorithm About the readerFor readers who know the basics of Python. No prior data science or machine learning skills required. About the authorLeonard Apeltsin is the Head of Data Science at Anomaly, where his team applies advanced analytics to uncover healthcare fraud, waste, and abuse. Table of ContentsCASE STUDY 1 FINDING THE WINNING STRATEGY IN A CARD GAME1 Computing probabilities using Python2 Plotting probabilities using Matplotlib3 Running random simulations in NumPy4 Case study 1 solutionCASE STUDY 2 ASSESSING ONLINE AD CLICKS FOR SIGNIFICANCE5 Basic probability and statistical analysis using SciPy6 Making predictions using the central limit theorem and SciPy7 Statistical hypothesis testing8 Analyzing tables using Pandas9 Case study 2 solutionCASE STUDY 3 TRACKING DISEASE OUTBREAKS USING NEWS HEADLINES10 Clustering data into groups11 Geographic location visualization and analysis12 Case study 3 solutionCASE STUDY 4 USING ONLINE JOB POSTINGS TO IMPROVE YOUR DATA SCIENCE RESUME13 Measuring text similarities14 Dimension reduction of matrix data15 NLP analysis of large text datasets16 Extracting text from web pages17 Case study 4 solutionCASE STUDY 5 PREDICTING FUTURE FRIENDSHIPS FROM SOCIAL NETWORK DATA18 An introduction to graph theory and network analysis19 Dynamic graph theory techniques for node ranking and social network analysis20 Network-driven supervised machine learning21 Training linear classifiers with logistic regression22 Training nonlinear classifiers with decision tree techniques23 Case study 5 solution", "item_img_path" : "https://covers2.booksamillion.com/covers/bam/1/61/729/625/1617296252_b.jpg", "price_data" : { "retail_price" : "59.99", "online_price" : "59.99", "our_price" : "59.99", "club_price" : "59.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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