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Mastering Python for Data Science
RSD 1915
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Детаљи о производу
| Publisher | Packt Publishing |
| Publication date | August 31, 2015 |
| Language | English |
| Print length | 356 pages |
| ISBN-10 | 1784390151 |
| ISBN-13 | 978-1784390150 |
| Item Weight | 1.12 pounds (510 grams) |
| Dimensions | 7.5 x 0.67 x 9.25 inches (19.1 x 1.7 x 23.5 cm) |
OPIS PROIZVODA
Mastering Python for Data Science
Питања и одговори купаца
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Pitanje:
Како купити Mastering Python for Data Science на мрежи од Убуи-а?
Odgovor: Лако је куповати Mastering Python for Data Science на мрежи од Убуи-а.. Морате само да потражите производ, изаберете начин испоруке приликом одјављивања и да га испоручите на вашу локацију. -
Pitanje:
Да ли је Mastering Python for Data Science доступан за онлајн куповину у Serbia?
Odgovor: Да, у Убуи Serbia овај производ је доступан за куповину по разумној цени.. Mastering Python for Data Science није доступан локално, али можете нам веровати у наше услуге експресне испоруке. -
Pitanje:
Колико времена је потребно да се производ добије након наручивања?
Odgovor: Време испоруке вашег нарученог производа варира у зависности од тога шта сте наручили и начина испоруке који сте изабрали.. Процењено време испоруке се помиње током процеса плаћања, па будите безбрижни док купујете.
Data Mining Editorial Review
**** The product in question, a book aimed at introducing readers to data science with Python, elicits a mix of impressions from its audience. Several reviewers appreciate its broad coverage and the practical utility it provides, especially for those who have some familiarity with Python. The initial chapters offer a solid primer on essential libraries like Numpy and Pandas, which can benefit beginners, while also diving into statistical examples and canonical machine learning algorithms that even experienced programmers may find valuable. However, the book faces Considerable criticism for its editorial quality, featuring numerous typos and awkward grammatical Constructions that diminish its credibility. Many readers have noted that certain explanations are dense and confusing, leaving novice readers struggling to grasp key concepts. The clarity of figures and tables is another pain point, as blurry images make it challenging to absorb intricate details. The feedback also indicates that while the book serves as a decent reference—especially for those already familiar with Python—its lack of depth and clarity may alienate newcomers to the field of data science. In summary, while the book demonstrates potential as a resourceful tool for those already versed in Python, it falls short in delivering a user-friendly learning experience for complete beginners, raising questions about its overall educational value. **
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Прос
- Broad coverage of significant topics in data science with Python.
- Useful for experienced Python programmers entering data science.
- Contains practical examples and unique Python statistical techniques.
- Quick pace that allows readers to become acquainted with key concepts swiftly.
Цонс
- Many explanations and concepts are vague and not well-articulated.
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RSD 1915
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