/cgi-bin/koha/opac-search.pl?q=ccl=su%3A%22DATA%20SCIENCE%20%22&sort_by=relevance&format=rss 11 0 50 ISBN:9789351194378 /cgi-bin/koha/opac-detail.pl?biblionumber=4679 ]]> By Zumel, Nina .
New Delhi Dreamtech | Wiley imprint 2014 .
xxiv; 389 , Part 1 Introduction to data science · The data science process · Loading data into R · Exploring data · Managing data Part 2 Modeling methods · Choosing and evaluating models · Memorization methods · Linear and logistic regression · Unsupervised methods · Exploring advanced methods Part 3 Delivering results · Documentation and deployment · Producing effective presentations 9789351194378

]]> Place hold on Practical Data Science With R

]]> /cgi-bin/koha/opac-detail.pl?biblionumber=4679 ISBN:9789351194378 /cgi-bin/koha/opac-detail.pl?biblionumber=4680 ]]> By Zumel, Nina .
New Delhi Dreamtech | Wiley imprint 2014 .
xxiv; 389 , Part 1 Introduction to data science · The data science process · Loading data into R · Exploring data · Managing data Part 2 Modeling methods · Choosing and evaluating models · Memorization methods · Linear and logistic regression · Unsupervised methods · Exploring advanced methods Part 3 Delivering results · Documentation and deployment · Producing effective presentations 9789351194378

]]> Place hold on Practical Data Science With R

]]> /cgi-bin/koha/opac-detail.pl?biblionumber=4680 ISBN:9789386173676 /cgi-bin/koha/opac-detail.pl?biblionumber=6463 ]]> By Jain, V.K. .
New Delhi Khanna Book 2018 .
viii, 267 9789386173676

]]> Place hold on Data science and analytics

]]> /cgi-bin/koha/opac-detail.pl?biblionumber=6463 ISBN:9789352139835 /cgi-bin/koha/opac-detail.pl?biblionumber=11718 ]]> By Vaughan, Daniel.
New Delhi Shroff publishers & Distributors 2020 .
xii, 228 , Includes index 9789352139835

]]> Place hold on Analytical skills for AI and data science

]]> /cgi-bin/koha/opac-detail.pl?biblionumber=11718 ISBN:9789355429827 /cgi-bin/koha/opac-detail.pl?biblionumber=13740 ]]> By Wickham, Hadley .
Navi Mumbai Shroff 2023 .
xxiii, 550 , Includes index 9789355429827

]]> Place hold on R for Data science

]]> /cgi-bin/koha/opac-detail.pl?biblionumber=13740 ISBN:9781032708379 /cgi-bin/koha/opac-detail.pl?biblionumber=13741 ]]> By Ismay, Chester .
New York CRC Press 2025 .
xxxiv, 456 , Includes index & bibliographies 9781032708379

]]> Place hold on Statistical inference via data science

]]> /cgi-bin/koha/opac-detail.pl?biblionumber=13741 ISBN:9788194722977 /cgi-bin/koha/opac-detail.pl?biblionumber=13750 ]]> Kolkata Shroff publishers 2021 .
xx, 228 , Includes index & appendix 9788194722977

]]> Place hold on Data governance

]]> /cgi-bin/koha/opac-detail.pl?biblionumber=13750 ISBN:9789352138326 /cgi-bin/koha/opac-detail.pl?biblionumber=13752 ]]> By Grus, Joel .
Navi Mumbai Shroff publishers 2019 .
xvii, 384 , Includes index 9789352138326

]]> Place hold on Data science from scratch

]]> /cgi-bin/koha/opac-detail.pl?biblionumber=13752 ISBN:9789355422743 /cgi-bin/koha/opac-detail.pl?biblionumber=13759 ]]> By Nield, Thomas .
Kolkata Shroff 2022 .
xiv, 332 9789355422743

]]> Place hold on Essentials Math for Data Science

]]> /cgi-bin/koha/opac-detail.pl?biblionumber=13759 ISBN:9789393330345 /cgi-bin/koha/opac-detail.pl?biblionumber=14004 ]]> By Arora, Sandhya .
Hyderabad Universities Press 2023 .
x, 488 , Includes index 9789393330345

]]> Place hold on Data science and analytics with Python

]]> /cgi-bin/koha/opac-detail.pl?biblionumber=14004 ISBN:9789393330345 /cgi-bin/koha/opac-detail.pl?biblionumber=14340 ]]> By Arora, Sandhya .
Hyderabad Universities Press 2023 .
x, 488 , Preface Acknowledgements Chapter 1: Introduction to Data Science Introduction | Data Science | Data Science Stages | Data Science Ecosystem | Tools Used in Data Science | Data Science Workflow | Automated Methods for Data Collection | Overview of Data | Sources of Data | Big Data | Data Categorization Chapter 2: Environment Set-up and Basics of Python Introduction to Python | Features of Python | Installation of Python | Python Identifiers | Python Indentation | Comments in Python | Basic Data | Operators and Expressions | Data Types | Sets and Frozen Sets | Loops and Conditions | Classes and Functions | Working with Files Chapter 3: NumPy and pandas Arrays | NumPy | The pandas Package | Panels Chapter 4: Data Visualization Introduction | Visualization Software and Tools | Interactive Visual Analysis | Text Visualization | Creating Graphs with Matplotlib | Creating Graphs with the plotly Package | Data Visualization with Matplotlib, Seaborn and pandas | Exploratory Data Analysis | Mapping and Cartopy Chapter 5: Python scikit-learn Introduction | Features of scikit-learn | Installation | Regression and Classifiers in scikit-learn | Support Vector Machine (SVM) | K-Nearest Neighbor (K-NN) | Case Studies Chapter 6: Environment Set-up: TensorFlow and Keras Introduction to TensorFlow | TensorFlow Features | Benefits of TensorFlow | Installation of TensorFlow | TensorFlow Architecture | Introduction to Keras | Installation of Keras | Features of Keras | Programming in Keras Chapter 7: Probability Introduction to Probability | Probability and Statistics | Random Variables | Central Limit Theorem | Density Functions | Probability Distribution Chapter 8: Machine Learning and Data Pre-processing Introduction to Machine Learning | Need for Machine Learning | Types of Machine Learning | Understanding Data | Data Set and Data Types | Data Pre-processing | Data Pre-processing in Python Chapter 9: Statistical Analysis: Descriptive Statistics Introduction | One-dimensional Statistics | Multi-dimensional Statistics | Simpson’s Paradox Chapter 10: Statistical Analysis: Inferential Statistics Introduction | Hypothesis Testing | Using the t-test | The t-test in Python | Chi-square Test | Wilcoxon Rank-Sum Test | Introduction to Analysis of Variance Chapter 11: Classification Introduction | K-NN Classification | Decision Trees | Support Vector Machine (SVM) | Naive Bayes’ Classification | Metrics for Evaluating Classifier Performance | Cross-validation | Ensemble Methods: Techniques to Improve Classification Accuracy Chapter 12: Prescriptive Analytics: Data Stream Mining Introduction to Stream Concepts | Mining Data Streams | Data Stream Management System (DSMS) | Data Stream Models | Data Stream Filtering | Sampling Data in a Stream | Concept Drift | Data Stream Classification | Rare Class Problem | Issues, Controversies and Problems | Applications of Data Mining | Implementation of Data Streams in Python Chapter 13: Language Data Processing in Python Natural Language Processing | Text Processing in Python | CGI/Web Programming Using Python | Twitter Sentiment Analysis in Python | Twitter Sentiment Analysis for Film Reviews | Case Study: A Recommendation System for a Film Data Set | Case Study: Text Mining and Visualization in Word Clouds Chapter 14: Clustering Introduction | Distance Measures | K-means Clustering | Hierarchical Clustering | DBSCAN Clustering Chapter 15: Association Rule Mining Introduction | The Apriori Algorithm | An Example of an Apriori Algorithm | An Example Using Python: Transactions in a Grocery Store Chapter 16: Time Series Analysis Using Python Introduction | Components of a Time Series | Additive and Multiplicative Time Series | Time Series Analysis | Case Study on Time Series Analysis Chapter 17: Deep Neural Network and Convolutional Neural Network Overview of Feed Forward Neural Network | Overview of Deep Neural Network | Activation Function | Loss Functions | Regularization | Convolutional Neural Network | Implementation of CNN | Case Studies Chapter 18: Case Studies Digit Recognition | Face and Eye Detection in Images | Correlation and Feature Selection | Fake News Detection | Detecting Duplicate Questions | Weather Prediction and Song Recommendation System | Spam Detection Index 9789393330345

]]> Place hold on Data science and analytics with python

]]> /cgi-bin/koha/opac-detail.pl?biblionumber=14340