Tabla de Contenidos: “…Application scenarios; 2.7.1. Forest fire detection scenario; 2.7.1.1. Introduction; 2.7.1.2. …”

Tabla de Contenidos: “…EQUIPO INTEGRADO PARA EL APROVECHAMIENTO (...) -- 41. PLANTACIÓN FORESTAL DE 2 AÑOS. ESTABLECIDA (...) -- 42. VIVERO FAMILIAR. …”

Tabla de Contenidos: “…-- Hyperparameter zur Regularisierung -- Regression -- Instabilität -- Übungen -- Kapitel 7: Ensemble Learning und Random Forests…”

Tabla de Contenidos: “…-- The history and evolution of natural language processing -- Initial strategies in the machine processing of natural language -- A winning synergy - the coming together of NLP and ML -- Introduction to math and statistics in NLP -- Understanding language models - ChatGPT example -- Summary -- Questions and answers -- Chapter 2: Linear Algebra, Probability and Statistics, and Estimation for Machine Learning and Natur -- Introduction to linear algebra -- Basic operations on matrices and vectors -- Matrix definitions -- Eigenvalues and eigenvectors -- Numerical methods for finding eigenvectors -- Eigenvalue decomposition -- Singular value decomposition -- Basic probability for machine learning -- Statistically independent -- Discrete random variables and their distribution -- Probability density function -- Bayesian estimation -- Summary -- Further reading -- References -- Chapter 3: Machine Learning for Natural Language Processing -- Technical requirements -- Data exploration -- Data visualization -- Data cleaning -- Feature selection -- Feature engineering -- Common machine learning models -- Linear regression -- Logistic regression -- Decision trees -- Random forest -- Support vector machines (SVMs) -- Neural networks and transformers -- Model underfitting and overfitting -- Splitting data -- Hyperparameter tuning -- Ensemble models -- Bagging -- Boosting -- Stacking -- Random forests -- Gradient boosting -- Handling imbalanced data -- SMOTE -- The NearMiss algorithm -- Cost-sensitive learning -- Data augmentation -- Dealing with correlated data -- Summary -- References…”

Tabla de Contenidos: “…Smith Quantifying Drivers of Coastal Forest Carbon Decline Highlights Opportunities for Targeted Human Interventions Reprinted from: Land 2021, 10, 752, doi:10.3390/land10070752 315.…”

Tabla de Contenidos: “…Holiday home (Göd, Hungary) / Imre Makovecz. Forest culture house (Visegrad, Hungary) / Imre Makovecz. …”

Tabla de Contenidos: “…Knowing what to do if there's no TPM module -- Performing Printer-Related Tasks -- Using the Printer Install Wizard -- Configuring print options -- Configuring the Print Server role -- Connecting to a Printer on a Print Server -- Performing Other Configuration Tasks -- Keyboard -- Mouse -- Power management -- Sound -- Language -- Fonts -- Chapter 3 Using the Control Panel -- Accessing the Control Panel -- Configuring the Control Panel -- Understanding Control Panel Items -- Chapter 4 Working with Workgroups -- Knowing What a Workgroup Is -- Knowing If a Workgroup Is Right for You -- Comparing Centralized and Group Sharing -- Configuring a Server for a Workgroup -- Changing the name of your workgroup -- Adding groups -- Creating users and adding users to the group -- Adding shared resources -- Managing Workgroups -- The Computer Management console -- The User Account window -- PowerShell -- Examining the Peer Name Resolution Protocol -- Chapter 5 Promoting Your Server to Domain Controller -- Understanding Domains -- What is a domain? -- Forests and domains and OUs, oh my! -- Understanding privileged domain groups -- Examining Flexible Single Master Operation roles on domain controllers -- Preparing to Create a Domain -- Functional levels -- Forest functional level -- Domain functional level -- Performing Domain Configuration Prerequisites -- Checking for unsupported roles and features -- Installing and configuring Domain Name System -- Installing and configuring Dynamic Host Configuration Protocol -- Configuring the Server as a Domain Controller -- Installing Active Directory Domain Services -- Configuring Active Directory Domain Services -- Converting your DNS Zone to an Active Directory Integrated Zone -- Authorizing your DHCP Server for your Active Directory environment -- Configuring the user accounts -- Sharing resources on a domain…”

Tabla de Contenidos: “…-- Technical requirements -- Detecting fake news using NLP -- Fake news classification with random forest -- About the dataset -- Importing useful libraries -- Reading and verifying the data -- NULL value check -- Combining title and text into a single column -- Cleaning and pre-processing data -- Separating the data and labels -- Converting text into numeric data -- Splitting the data -- Defining the random forest classifier -- Training the model -- Predicting the test data -- Checking the results/metrics on the test dataset -- Confusion matrix -- Launching model training on Vertex AI -- Setting configurations -- Initializing the Vertex AI SDK -- Defining the Vertex AI training job -- Running the Vertex AI job -- BERT-based fake news classification -- BERT for fake news classification -- Importing useful libraries -- The dataset -- Data preparation -- Splitting the data -- Creating data loader objects for batching -- Loading the pre-trained BERT model -- Scheduler -- Training BERT…”

Tabla de Contenidos: “…Creating reports in Data Studio -- Summary -- Chapter 5: Transforming Your Data -- How to clean and prepare the data -- Google Cloud Dataprep -- Exploring Dataprep console -- Removing empty cells -- Replacing incorrect values -- Mismatched values -- Finding outliers in the data -- Visual functionality -- Statistical information -- Removing outliers -- Run Job -- Scale of features -- Min-max normalization -- z score standardization -- Google Cloud Dataflow -- Summary -- Chapter 6: Essential Machine Learning -- Applications of machine learning -- Financial services -- Retail industry -- Telecom industry -- Supervised and unsupervised machine learning -- Overview of machine learning techniques -- Objective function in regression -- Linear regression -- Decision tree -- Random forest -- Gradient boosting -- Neural network -- Logistic regression -- Objective function in classification -- Data splitting -- Measuring the accuracy of a model -- Absolute error -- Root mean square error -- The difference between machine learning and deep learning -- Applications of deep learning -- Summary -- Chapter 7: Google Machine Learning APIs -- Vision API -- Enabling the API -- Opening an instance -- Creating an instance using Cloud Shell -- Label detection -- Text detection -- Logo detection -- Landmark detection -- Cloud Translation API -- Enabling the API -- Natural Language API -- Speech-to-text API -- Video Intelligence API -- Summary -- Chapter 8: Creating ML Applications with Firebase -- Features of Firebase -- Building a web application -- Building a mobile application -- Summary -- Chapter 9: Neural Networks with TensorFlow and Keras -- Overview of a neural network -- Setting up Google Cloud Datalab -- Installing and importing the required packages -- Working details of a simple neural network -- Backpropagation -- Implementing a simple neural network in Keras…”

Tabla de Contenidos: “…Snowball stemming -- Lancaster stemming -- Lovins stemming -- Dawson stemming -- Lemmatization -- N-grams -- Feature extraction -- One hot encoding -- TF-IDF -- CountVectorizer -- Word2Vec -- CBOW -- Skip-Gram model -- Applying NLP techniques -- Text classification -- Introduction to Naive Bayes' algorithm -- Random Forest -- Naive Bayes' text classification code example -- Implementing sentiment analysis -- Frequently asked questions -- Summary -- Chapter 7: Fuzzy Systems -- Fuzzy logic fundamentals -- Fuzzy sets and membership functions -- Attributes and notations of crisp sets -- Operations on crisp sets -- Properties of crisp sets -- Fuzzification -- Defuzzification -- Defuzzification methods -- Fuzzy inference -- ANFIS network -- Adaptive network -- ANFIS architecture and hybrid learning algorithm -- Fuzzy C-means clustering -- NEFCLASS -- Frequently asked questions -- Summary -- Chapter 8: Genetic Programming -- Genetic algorithms structure -- KEEL framework -- Encog machine learning framework -- Encog development environment setup -- Encog API structure -- Introduction to the Weka framework -- Weka Explorer features -- Preprocess -- Classify -- Attribute search with genetic algorithms in Weka -- Frequently asked questions -- Summary -- Chapter 9: Swarm Intelligence -- Swarm intelligence -- Self-organization -- Stigmergy -- Division of labor -- Advantages of collective intelligent systems -- Design principles for developing SI systems -- The particle swarm optimization model -- PSO implementation considerations -- Ant colony optimization model -- MASON Library -- MASON Layered Architecture -- Opt4J library -- Applications in big data analytics -- Handling dynamical data -- Multi-objective optimization -- Frequently asked questions -- Summary -- Chapter 10: Reinforcement Learning -- Reinforcement learning algorithms concept…”

Tabla de Contenidos: “…5.5.1 Dairy Production in Low-Productivity Areas -- 5.5.2 Meat Production in Low-Productivity Areas -- 5.6 Radionuclide Transfer to Game Animals -- 5.6.1 Forest Environments -- 5.7 Impacts on the Health of Livestock Exposed to Nuclear Contamination -- 5.8 Routes of Radionuclide Intake via Aquatic Pathways -- 5.8.1 Radionuclides in Freshwater Fish -- 5.9 The Risk for Public Health (Placement on the Market for Human Consumption) -- 5.9.1 Radioiodine -- 5.9.2 Radiocaesium -- 5.9.3 Other Radionuclides -- References -- Chapter 6: Management Options for Animal Production Systems: Which Ones to Choose in the Event of a Nuclear or Radiological Emergency? …”

Tabla de Contenidos: “…-- Earthquakes -- Hurricanes -- Tornadoes -- Tsunamis -- Floods and Levee Breaks -- Volcanic Eruptions -- Forest Fires -- Landslides and Debris Flows -- Pandemics -- Hazardous Material Spills or Releases -- Food or Product Contamination and Animal Disease Outbreaks -- Severe Storms and Cold Weather -- Drought and Extreme Heat Conditions -- Structural Collapse -- Hostage Taking, Riots, and Targeted Violence -- Space Weather -- Chapter Summary -- Chapter Quiz -- Notes -- Part 4 Homeland Security In Action: Programs and Activities -- Chapter 16 Critical Infrastructure Protection and Key Assets: Protecting America's Most Important Targets -- Chapter Overview -- Chapter Learning Objectives -- Lifeblood of the U.S. …”

“…This book presents some of the ideas and understanding about geomorphology: <br /><br />Learn about the effect of deforestation and then reforestation on river channel morphology. …”

Tabla de Contenidos: “…Gallen ; Proap : Parque Lineal de Ourém ; PWP Landscape Architecture : Kiel Triangle Plaza, Plaza Saitama ; Roderschall Landschaftarchitekten : Parque MFO ; Ravetllat & Ribas Arquitectes : Passeig Garcia Fària ; RCR Aranda Pigem Vilalta Arquitectes : Parque de Pedra Tosca ; Rosa Grena Kliass Arquitetura Paisagística : Parque da Juventude ; Rush & Wright Associates : Grand Plaza, The Centre for Ideas ; Santa-Rita Arquitectos : Parque urbano de Beja ; Scapelab : Renovación de la plaza Cufarjev ; SLA : Jardín Charlotte ; SMC Alsop : Reurbanización de Clarke Quay ; Stoa Architecture : Remodelación del Rauba Capeu ; Studio Lazzaretto : Plaza Vittorio Veneto ; Taylor Cullity Lethlean : Galeria Forest ; Tod Saunders - Saunders Architecture : Mirador Aurland ; Tommie Wilhelmsen - Sivilarkitekt MNAL : Mirador Aurland ; Toyo Ito & Architects Associates : Fira Montjuïc 2 en Barcelona ; Turenscape : Plaza Dujiangyan, Parque Zhongshan Shipyard ; Urbanus Architecture & Design : Diwang Park B, Sungang Central Plaza ; Verzone Woods Architectes : Parques y jardines Las Margas ; Vetsch Nipkow Partner Landschaftsarchitekten : Katharina Sulzer Platz ; Vladimir Djurovic Landscape Architecture : Jardín Square Four ; West 8 : Parque One-North ; Zade & Vilà Associats : Bosque de la vida…”

Tabla de Contenidos: “…-- Self-classifying decision trees and AI tools -- Entropy -- One hot encoding -- Random forests -- Grid searching and A* (A-Star) -- The A* algorithm -- D* (D-Star or Dynamic A*) -- GPS path finding does not use a map! …”

Tabla de Contenidos: “…Cover -- Title Page -- Copyright and Credits -- Acknowledgments -- Contributors -- Table of Contents -- Preface -- Chapter 1: Introducing Machine Learning for Text -- The language phenomenon -- The data explosion -- The era of AI -- Relevant research fields -- The machine learning paradigm -- Taxonomy of machine learning techniques -- Supervised learning -- Unsupervised learning -- Semi-supervised learning -- Reinforcement learning -- Visualization of the data -- Evaluation of the results -- Summary -- Chapter 2: Detecting Spam Emails -- Technical requirements -- Understanding spam detection -- Explaining feature engineering -- Extracting word representations -- Using label encoding -- Using one-hot encoding -- Using token count encoding -- Using tf-idf encoding -- Executing data preprocessing -- Tokenizing the input -- Removing stop words -- Stemming the words -- Lemmatizing the words -- Performing classification -- Getting the data -- Creating the train and test sets -- Preprocessing the data -- Extracting the features -- Introducing the Support Vector Machines algorithm -- Understanding Bayes' theorem -- Measuring classification performance -- Calculating accuracy -- Calculating precision and recall -- Calculating the F-score -- Creating ROC and AUC -- Creating precision-recall curves -- Summary -- Chapter 3: Classifying Topics of Newsgroup Posts -- Technical requirements -- Understanding topic classification -- Performing exploratory data analysis -- Executing dimensionality reduction -- Understanding principal component analysis -- Understanding linear discriminant analysis -- Putting PCA and LDA into action -- Introducing the k-nearest neighbors algorithm -- Performing feature extraction -- Performing cross-validation -- Performing classification -- Comparison to the baseline model -- Introducing the random forest algorithm…”

Tabla de Contenidos: “…-- Navigating the Platform -- Introducing Jupyter Notebooks -- Jupyter Features -- Exploring some of Jupyter's most useful features -- Converting a Jupyter Notebook to a Python Script -- Python Libraries -- Import the external libraries and set up the plotting environment -- Our First Analysis - The Boston Housing Dataset -- Loading the Data into Jupyter Using a Pandas DataFrame -- Load the Boston housing dataset -- Data Exploration -- Explore the Boston housing dataset -- Introduction to Predictive Analytics with Jupyter Notebooks -- Linear models with Seaborn and scikit-learn -- Activity: Building a Third-Order Polynomial Model -- Linear models with Seaborn and scikit-learn -- Using Categorical Features for Segmentation Analysis -- Create categorical fields from continuous variables and make segmented visualizations -- Summary -- Chapter 2: Data Cleaning and Advanced Machine Learning -- Preparing to Train a Predictive Model -- Determining a Plan for Predictive Analytics -- Preprocessing Data for Machine Learning -- Exploring data preprocessing tools and methods -- Activity: Preparing to Train a Predictive Model for the Employee-Retention Problem -- Training Classification Models -- Introduction to Classification Algorithms -- Training two-feature classification models with scikit-learn -- The plot_decision_regions Function -- Training k-nearest neighbors for our model -- Training a Random Forest -- Assessing Models with k-Fold Cross-Validation and Validation Curves -- Using k-fold cross-validation and validation curves in Python with scikit-learn -- Dimensionality Reduction Techniques…”

Tabla de Contenidos: “…Wright : casa Roberts, River Forest ; E. Lutyens : casa Goddards, Abinger ; M.H. …”

Tabla de Contenidos: “…The Royal Scots Dragoon Guards - Flowers Of The Forest 10. The Proclaimers - Lets Get Married 11. …”