Tabla de Contenidos: “…Recommendation systems -- Getting started with networks -- Example - K-pop implementation -- Summary -- Further reading -- Chapter 3: Useful Python Libraries -- Technical requirements -- Using notebooks -- Data analysis and processing -- pandas -- NumPy -- Data visualization -- Matplotlib -- Seaborn -- Plotly -- NLP -- Natural Language Toolkit -- Setup -- Starter functionality -- Documentation -- spaCy -- Network analysis and visualization -- NetworkX -- scikit-network -- ML -- scikit-learn -- Karate Club -- spaCy (revisited) -- Summary -- Part 2: Graph Construction and Cleanup -- Chapter 4: NLP and Network Synergy -- Technical requirements -- Why are we learning about NLP in a network book? …”

Tabla de Contenidos: “…Chapter 4: Bayesian Networks and Hidden Markov Models -- Conditional probabilities and Bayes' theorem -- Bayesian networks -- Sampling from a Bayesian network -- Direct sampling -- Example of direct sampling -- A gentle introduction to Markov chains -- Gibbs sampling -- Metropolis-Hastings sampling -- Example of Metropolis-Hastings sampling -- Sampling example using PyMC3 -- Hidden Markov Models (HMMs) -- Forward-backward algorithm -- Forward phase -- Backward phase -- HMM parameter estimation -- Example of HMM training with hmmlearn -- Viterbi algorithm -- Finding the most likely hidden state sequence with hmmlearn -- Summary -- Chapter 5: EM Algorithm and Applications -- MLE and MAP learning -- EM algorithm -- An example of parameter estimation -- Gaussian mixture -- An example of Gaussian Mixtures using Scikit-Learn -- Factor analysis -- An example of factor analysis with Scikit-Learn -- Principal Component Analysis -- An example of PCA with Scikit-Learn -- Independent component analysis -- An example of FastICA with Scikit-Learn -- Addendum to HMMs -- Summary -- Chapter 6: Hebbian Learning and Self-Organizing Maps -- Hebb's rule -- Analysis of the covariance rule -- Example of covariance rule application -- Weight vector stabilization and Oja's rule -- Sanger's network -- Example of Sanger's network -- Rubner-Tavan's network -- Example of Rubner-Tavan's network -- Self-organizing maps -- Example of SOM -- Summary -- Chapter 7: Clustering Algorithms -- k-Nearest Neighbors -- KD Trees -- Ball Trees -- Example of KNN with Scikit-Learn -- K-means -- K-means++ -- Example of K-means with Scikit-Learn -- Evaluation metrics -- Homogeneity score -- Completeness score -- Adjusted Rand Index -- Silhouette score -- Fuzzy C-means -- Example of fuzzy C-means with Scikit-Fuzzy -- Spectral clustering -- Example of spectral clustering with Scikit-Learn -- Summary…”

“…This book explains how to structure the clean data obtained and store in MongoDB using PyMongo. You will also perform web scraping and visualize data using Scrappy and Beautifulsoup. …”

Tabla de Contenidos: “…SKILL 5 - functional programming -- Must-know advanced Python skills -- SKILL 1 - understand the concepts of OOP and how to apply them in Python -- SKILL 2 - know how to work with advanced data structures in Python, such as dictionaries and sets -- SKILL 3 - be familiar with Python's built-in data manipulation and analysis libraries, such as NumPy and pandas -- SKILL 4 - understand how to work with regular expressions in Python -- SKILL 5 - recursion -- Technical interview questions -- Python interview questions -- Data engineering interview questions -- General technical concept questions -- Summary -- Chapter 6: Unit Testing -- Fundamentals of unit testing -- Importance of unit testing -- Unit testing frameworks in Python -- Process of unit testing -- Must-know intermediate unit testing skills -- Parameterized tests -- Performance and stress testing -- Various scenario testing techniques -- Unit testing interview questions -- Summary -- Chapter 7: Database Fundamentals -- Must-know foundational database concepts -- Relational databases -- NoSQL databases -- OLTP versus OLAP databases -- Normalization -- Must-know advanced database concepts -- Constraints -- ACID properties -- CAP theorem -- Triggers -- Technical interview questions -- Summary -- Chapter 8: Essential SQL for Data Engineers -- Must-know foundational SQL concepts -- Must-know advanced SQL concepts -- Technical interview questions -- Summary -- Part 3: Essentials for Data Engineers Part II -- Chapter 9: Database Design and Optimization -- Understanding database design essentials -- Indexing -- Data partitioning -- Performance metrics -- Designing for scalability -- Mastering data modeling concepts -- Technical interview questions -- Summary -- Chapter 10: Data Processing and ETL -- Fundamental concepts -- The life cycle of an ETL job…”

Tabla de Contenidos: “…-- No servers to manage -- Pay-per-invocation billing model -- Ability to automatically scale with usage -- Built-in availability and fault tolerance -- Design patterns -- When to use serverless -- The sweet spot -- Classes of serverless pattern -- Three-tier web application patterns -- ETL patterns -- Big data patterns -- Automation and deployment patterns -- Serverless frameworks -- Summary -- Chapter 2: A Three-Tier Web Application Using REST -- Serverless tooling -- System architecture -- Presentation layer -- Logic layer -- Data layer -- Logic layer -- Application code and function layout -- Organization of the Lambda functions -- Organization of the application code -- Configuration with environment variables -- Code structure -- Function layout -- Presentation layer -- File storage with S3 -- CDN with CloudFront -- Data layer -- Writing our logic layer -- Application entrypoint -- Application logic -- Wiring handler.py to Lambda via API Gateway -- Deploying the REST API -- Deploying the Postgres database -- Setting up static assets -- Viewing the deployed web application -- Running tests -- Iteration and deployment -- Deploying the entire stack -- Deploying the application code -- Summary -- Chapter 3: A Three-Tier Web Application Pattern with GraphQL -- Introduction to GraphQL -- System architecture -- Logic layer -- Organization of the Lambda functions -- Organization of the application code -- Function layout -- Presentation layer -- Writing the logic layer -- Implementing the entry point -- Implementing GraphQL queries -- Implementing GraphQL mutations -- Deployment -- Viewing the deployed application -- Iteration and deployment -- Summary…”

Tabla de Contenidos: “…-- Redis Stack deployment types -- Summary -- Chapter 2: Developing Modern Use Cases with Redis Stack -- Technical requirements -- Caching, rate-limiting, geo-positioning, and other Redis traditional use cases -- Caching -- Session store -- Rate limiter -- Leaderboards -- Data deduplication -- Geo-positioning -- Message processing and delivery -- Going beyond the real-time cache with Redis Stack -- Querying, indexing, and search -- Monitoring and analysis -- Fraud detection -- Feature store for machine learning -- Designing microservice architectures with Redis Stack -- API gateway -- Summary -- Chapter 3: Getting Started with Redis Stack -- Installing Redis Stack using binary packages -- Installing Redis Stack using native packages -- macOS-native package -- Linux-native package -- Running Redis Stack using Docker -- Using Redis Cloud -- Installing RedisInsight -- Installing the Redis Stack client libraries -- Java client library -- JavaScript client library -- Python client library -- Golang client library -- C#/.NET client library -- Running health checks -- Summary -- Chapter 4: Setting Up Client Libraries -- Technical requirements -- Redis Stack client libraries -- Programming in Python using redis-py -- Storing information in Redis Stack using Python -- Redis OM for Python -- Programming in Java using Jedis -- Storing information in Redis Stack using Java -- Redis OM for Java…”

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