عنوان
پدید آورنده
موضوع
رده
QA76.73.P98
QA76
.
73
.
P98
کتابخانه
محل استقرار
شابک
شابک
1782161414 (electronic bk.)
شابک
9781782161417 (electronic bk.)
شابک اشتباه
9781782161400
شماره کتابشناسی ملی
شماره
b421640
عنوان و نام پديدآور
عنوان اصلي
Building Machine Learning Systems with Python
نام عام مواد
[Book]
مشخصات ظاهری
نام خاص و کميت اثر
1 online resource (290 pages)
يادداشت کلی
متن يادداشت
Description based upon print version of record
یادداشتهای مربوط به مندرجات
متن يادداشت
Cover; Copyright; Credits; About the Authors; About the Reviewers; www.PacktPub.com; Table of Contents; Preface; Chapter 1: Getting Started with Python Machine Learning; Machine learning and Python -- the dream team; What the book will teach you (and what it will not); What to do when you are stuck; Getting started; Introduction to NumPy, SciPy, and Matplotlib; Installing Python; Chewing data efficiently with NumPy and intelligently with SciPy; Learning NumPy; Indexing; Handling non-existing values; Comparing runtime behaviors; Learning SciPy; Our first (tiny) machine learning application
متن يادداشت
A more complex dataset and a more complex classifierLearning about the Seeds dataset; Features and feature engineering; Nearest neighbor classification; Binary and multiclass classification; Summary; Chapter 3: Clustering -- Finding Related Posts; Measuring the relatedness of posts; How not to do it; How to do it; Preprocessing -- similarity measured as similar number of common words; Converting raw text into a bag-of-words; Counting words; Normalizing the word count vectors; Removing less important words; Stemming; Installing and using NLTK; Extending the vectorizer with NLTK's stemmer
متن يادداشت
Looking behind accuracy -- precision and recall
متن يادداشت
Reading in the dataPreprocessing and cleaning the data; Choosing the right model and learning algorithm; Before building our first model; Starting with a simple straight line; Towards some advanced stuff; Stepping back to go forward -- another look at our data; Training and testing; Answering our initial question; Summary; Chapter 2: Learning How to Classify with Real-world Examples; The Iris dataset; The first step is visualization; Building our first classification model; Evaluation -- holding out data and cross-validation; Building more complex classifiers
متن يادداشت
Slimming the data down to chewable chunksPreselection and processing of attributes; Defining what is a good answer; Creating our first classifier; Starting with the k-nearest neighbor (kNN) algorithm; Engineering the features; Training the classifier; Measuring the classifier's performance; Designing more features; Deciding how to improve; Bias-variance and its trade-off; Fixing high bias; Fixing high variance; High bias or low bias; Using logistic regression; A bit of math with a small example; Applying logistic regression to our postclassification problem
متن يادداشت
Stop words on steroidsOur achievements and goals; Clustering; KMeans; Getting test data to evaluate our ideas on; Clustering posts; Solving our initial challenge; Another look at noise; Tweaking the parameters; Summary; Chapter 4: Topic Modeling; Latent Dirichlet allocation (LDA); Building a topic model; Comparing similarity in topic space; Modeling the whole of Wikipedia; Choosing the number of topics; Summary; Chapter 5: Classification -- Detecting Poor Answers; Sketching our roadmap; Learning to classify classy answers; Tuning the instance; Tuning the classifier; Fetching the data
بدون عنوان
0
بدون عنوان
8
بدون عنوان
8
بدون عنوان
8
بدون عنوان
8
بدون عنوان
8
یادداشتهای مربوط به خلاصه یا چکیده
متن يادداشت
This is a tutorial-driven and practical, but well-grounded book showcasing good Machine Learning practices. There will be an emphasis on using existing technologies instead of showing how to write your own implementations of algorithms. This book is a scenario-based, example-driven tutorial. By the end of the book you will have learnt critical aspects of Machine Learning Python projects and experienced the power of ML-based systems by actually working on them.This book primarily targets Python developers who want to learn about and build Machine Learning into their projects, or who want to pro
یادداشتهای مربوط به سفارشات
منبع سفارش / آدرس اشتراک
Safari Books Online
شماره انبار
CL0500000301
ویراست دیگر از اثر در قالب دیگر رسانه
عنوان
Building Machine Learning Systems with Python
شماره استاندارد بين المللي کتاب و موسيقي
9781782161400
قطعه
عنوان
Safari books online
موضوع (اسم عام یاعبارت اسمی عام)
موضوع مستند نشده
Machine learning.
موضوع مستند نشده
Python (Computer program language)
موضوع مستند نشده
Multimedia systems
موضوع مستند نشده
Programming languages (Electronic computers)
موضوع مستند نشده
Python (Computer program language)
مقوله موضوعی
موضوع مستند نشده
COM-- 000000
رده بندی ديویی
شماره
006
.
76
رده بندی کنگره
شماره رده
QA76
.
73
.
P98
نام شخص به منزله سر شناسه - (مسئولیت معنوی درجه اول )
مستند نام اشخاص تاييد نشده
Richert, Willi.
نام شخص - (مسئولیت معنوی برابر )
مستند نام اشخاص تاييد نشده
Coelho, Luis Pedro.
مبدا اصلی
تاريخ عمليات
20131101095755.0
قواعد فهرست نويسي ( بخش توصيفي )
rda
دسترسی و محل الکترونیکی
نام الکترونيکي
مطالعه متن کتاب اطلاعات رکورد کتابشناسی
نوع ماده
[Book]
اطلاعات دسترسی رکورد
تكميل شده
Y
