DLeX: AI Python
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هوش‌مصنوعی و برنامه‌نویسی

ارتباط :
https://twitter.com/NaviDDariya
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دوره یادگیری کورسرا
Introduction to Data Science in Python

20 Pandas Idioms

#فیلم #منابع #کورسرا #پایتون #علم_داده
#python

❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
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دوره یادگیری کورسرا
Introduction to Data Science in Python

21 Group By

#فیلم #منابع #کورسرا #پایتون #علم_داده
#python

❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
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دوره یادگیری کورسرا
Introduction to Data Science in Python

22 scales

#فیلم #منابع #کورسرا #پایتون #علم_داده
#python

❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
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دوره یادگیری کورسرا
Introduction to Data Science in Python

23 Pivot Table

#فیلم #منابع #کورسرا #پایتون #علم_داده
#python

❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
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دوره یادگیری کورسرا
Introduction to Data Science in Python

24 Date/Time Functionality

#فیلم #منابع #کورسرا #پایتون #علم_داده
#python

❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
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دوره یادگیری کورسرا
Introduction to Data Science in Python

25 Basic Statistical Testing

#فیلم #منابع #کورسرا #پایتون #علم_داده
#python

❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
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دوره یادگیری کورسرا
Introduction to Data Science in Python

26 Other Forms of Structured Data
قسمت پایانی

#فیلم #منابع #کورسرا #پایتون #علم_داده
#python

❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
Skills you need in the industry as a Data Scientist (in no particular order):

1. Web Scraping
2. Querying databases - Different flavours of SQL
3. Understanding basics of data storage, warehouses and data pipelines
4. Exploratory Data Analysis
5. Data Visualization
6. Hypothesis testing - A/B testing specifically
7. Writing effectively and clearly about your projects, results, tech used etc.
8. Communicating results to stakeholders
9. Understanding the business problem
10. Understanding the business impact of your solutions
11. Creating an API
12. Deploying Docker containers/virtual environments
13. Creating a basic GUI - specially for internal products and projects without a pre-existing frontend
14. Documentation of every important step and detail in your projects
15. Data Modeling
16. Feature Engineering
17. Building ML models
18. Monitoring ML models in production
19. Abstracting code whenever required
20. Making your projects more maintainable - specially when they're in/going to production
21. Helping juniors/colleagues unblock on technical issues
22. Creating relevant metrics
23. Ensuring data validation
24. Using a version control system - usually Git these days
25. Reading and understanding new research
26. Knowing basics of Data Structures, Algorithms, Memory Management, Multiprocessing etc.
27. Translating Business problems into Data problems
28. Stakeholder expectation management within your team and external teams
29. Understanding REST, SOAP and the technology behind them
30. Building, running and interpreting surveys

Important note:
- Not all of the above skills are needed all of the time!
But different Data Scientist roles will have different weightage assigned to combinations of the above skills. And you don't need to be an absolute expert at each of these.
Recognise your strengths.

Get good at all of the above to some level and then keep improving that level in the areas that matter more in your current role.

#منابع #علم_داده

❇️ @AI_Python
چگونه در مسابقات علم داده برنده بشیم: توصیه‌های برندگان Kaggle

https://www.coursera.org/learn/competitive-data-science

#منابع #علم_داده

❇️ @AI_Python
CS109 Data Science
By Harvard University

⌛️ 12 weeks
Video lectures
Slides
Lab exercises

🔗 http://cs109.github.io/2015/pages/videos.html

#علم_داده #منابع

❇️ @AI_Python
Many Data Science aspirants struggle to find good projects to get a start in Data science or #MachineLearning.

Here is the list of few #DataScience projects (found on kaggle), it covers Basics of Python, Advanced Statistics, #SupervisedLearning (Regression and Classification problems)

1. Basic #python and #statistics

Pima Indians : https://www.kaggle.com/uciml/pima-indians-diabetes-database

Cardio Goodness fit : https://www.kaggle.com/saurav9786/cardiogoodfitness

Automobile : https://www.kaggle.com/toramky/automobile-dataset

2. Advanced Statistics

Game of Thrones:
https://www.kaggle.com/mylesoneill/game-of-thrones

World University Ranking:
https://www.kaggle.com/mylesoneill/world-university-rankings

IMDB Movie Dataset: https://www.kaggle.com/carolzhangdc/imdb-5000-movie-dataset

3. Supervised Learning

a) Regression Problems

How much did it rain : https://www.kaggle.com/c/how-much-did-it-rain-ii/overview

Inventory Demand: https://www.kaggle.com/c/grupo-bimbo-inventory-demand

Property Inspection predictiion:
https://www.kaggle.com/c/liberty-mutual-group-property-inspection-prediction

Restaurant Revenue prediction:
https://www.kaggle.com/c/restaurant-revenue-prediction/data

IMDB Box office Prediction:
https://www.kaggle.com/c/tmdb-box-office-prediction/overview

b) Classification problems

Employee Access challenge :
https://www.kaggle.com/c/amazon-employee-access-challenge/overview

Titanic :
https://www.kaggle.com/c/titanic
San Francisco crime:
https://www.kaggle.com/c/sf-crime

Customer satisfcation:
https://www.kaggle.com/c/santander-customer-satisfaction
Trip type classification:

https://www.kaggle.com/c/walmart-recruiting-trip-type-classification

Categorize cusine:
https://www.kaggle.com/c/whats-cooking

#پروژه #منابع #الگوریتمها #یادگیری_ماشین #هوش_مصنوعی #علم_داده #پایتون

❇️ @AI_Python
کتاب
احتمال برای علم داده

https://probability4datascience.com/

#کتاب #منابع #علم_داده

❇️ @AI_Python
دانلود رایگان کتاب مقدمه ای بر علم داده: یادگیری زبان جولیا و با دیدگاهی بر ریاضیات در علم داده

1, Vectors
2. Matrices
3. Sigmoid
4. K Means Clustering
5. Gradient Descent

https://datascience-book.gitlab.io/

#کتاب #علم_داده #منابع
#DataScience #MachineLearning #ArtificialIntelligence #JuliaLang

❇️ @AI_Python
Forwarded from DLeX: AI Python (Farzad🦅)
فیلم آموزشی
«چطور از بین همه مدلهای یادگیری ماشین مدل مناسبی انتخاب کنیم؟»

#فیلم #آموزش #یادگیری_ماشین #منابع #علم_داده #آمار

🌎 Separating signal from noise

🌎 Choosing between candidates

🌎 Choosing an error function

🌎 Splitting the data

🌎 Choosing model candidates


❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
Forwarded from DLeX: AI Python (Farzad🦅🐋🐕🦏)
ویدیوهای آموزشی دوره پایتون برای علم داده - مدرس عسگری، نیکزاد
نیم فصل اول پایتون برای علم داده:
⭐️مقدمات و توضیحات کلی
1️⃣ https://t.me/ai_python/6923

⭐️شروع کار، متغیرها، اولین برنامه و لیست دیکشنری تاپل و ست
2️⃣ https://t.me/ai_python/6924

⭐️شرط ها و حلقه ها
3️⃣ https://t.me/ai_python/6927

⭐️توابع، توابع یک خطی، نگاشت و کاهش، فرمت دهی رشته ها
4️⃣ https://t.me/ai_python/6928

⭐️شی گرایی در پایتون جلسه اول
5️⃣ https://t.me/ai_python/6939

⭐️شی گرایی در پایتون جلسه دوم
6️⃣ https://t.me/ai_python/6949

این دوره ادامه دارد و ویدیوها در حال تکمیل شدن هستند. تا کنون ۶ جلسه قرار داده شده است.
#فیلم #پایتون #علم_داده #آموزش #منابع

❇️ @AI_Python
🗣 @AI_Python_Arxiv
✴️ @AI_Python_EN
Forwarded from DLeX: AI Python (Farzad🦅🐋🐕🦏)
نکاتی آموزشی

How to Choose Your AI Vendor

#یادگیری_ماشین #آمار #آموزش #علم_داده

🌎 Link Review

❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
Forwarded from DLeX: AI Python (Farzad)
Introduction_to_Descriptive_Statistics.pdf
418.8 KB
مقدمه ای بر آمار توصیفی و احتمال برای علم داده

#آمار #علم_داده #منابع #کتاب #الگوریتمها
#book #datascience

❇️ @AI_Python
🗣 @AI_Python_arXiv
✴️ @AI_Python_EN
کورس کلاس دانشگاه هاروارد به طور رایگان منتشر شد
Introduction to Data Science CS109A course materials by Harvard University are free and open for everyone!

1. Lecture notes
2. R code, Python notebooks
3. Lab material
4. Advanced sections

Learn here: https://harvard-iacs.github.io/2019-CS109A/pages/syllabus.html

#منابع #فیلم #آموزش_کلاسی #علم_داده

❇️ @AI_Python
Data Science

Python Tutorial for Beginners - Learn Python Programming from Scratch
Data Science with Python for Beginners - Full Course
Image Analysis with Convolutional Neural Networks and TensorFlow

https://www.youtube.com/playlist?list=PL7mOFdpoBB6QiW3_n7aKn_eHTCCftPJLw

#علم_داده #منابع #آموزش_کلاسی #فیلم
✳️ @AI_Python