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  Learning scientific with phython.pdf
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  Deep Learning and Data Labeling for Medical Applications.pdf
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  deep_learning_adaptive_computation.pdf
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  سلام
از دوستان اگر کسی پایان نامش مرتبط با موضوع«بهبود استخراج قوانین انجمني با استفاده از روش های تکاملي» هستش لطفا جهت همکاری به این ایدی پیام بدن. با تشکر
@mahdi7_7_7
  از دوستان اگر کسی پایان نامش مرتبط با موضوع«بهبود استخراج قوانین انجمني با استفاده از روش های تکاملي» هستش لطفا جهت همکاری به این ایدی پیام بدن. با تشکر
@mahdi7_7_7
Machine learning books and papers pinned «سلام از دوستان اگر کسی پایان نامش مرتبط با موضوع«بهبود استخراج قوانین انجمني با استفاده از روش های تکاملي» هستش لطفا جهت همکاری به این ایدی پیام بدن. با تشکر @mahdi7_7_7»
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  4_5801048860251915627.pdf
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  [Adrian_Rosebrock]_Deep_Learning_for_Computer_Vision.pdf
    26.4 MB
  p.y.b:
Here is a list of what I believe are the 10 Practical Steps for #DataScience:
1. Programming
a. Python - https://lnkd.in/gGQ7cuv
b. R - https://lnkd.in/giMGbph
c. SQL - https://lnkd.in/gM8nMNP
d. Command Line - https://lnkd.in/e3EQuis
2. Stats/Prob/Math
a. Coursera's Statistics w/ R - https://lnkd.in/gGT9NEf
b. edX's Probability - https://lnkd.in/gpUyC3P
c. Khan Academy Linear Algebra - https://lnkd.in/gMshbX4
3. Data Viz
a. Python Matplotlib- https://lnkd.in/gr3ifNt
b. R ggplot2 - https://lnkd.in/eThJXNr
4. Data Manipulation
a. Python Pandas - https://lnkd.in/g9kfpX4
b. R dplyr - https://lnkd.in/gAWusih
5. #MachineLearning
a. Google Crash Course - https://lnkd.in/gSgkVcT
b. Stanford Coursera - https://lnkd.in/g8ZG557
c. ISLR Book - https://lnkd.in/gk8GPZC
6. Experimental Design
a. Udacity A/B Testing - https://lnkd.in/gCerh4f
7. Business Sense
a. Metrics - https://lnkd.in/gZAG7bS
8. Communication
a. Storytelling - https://lnkd.in/gwjxVUu
9. Profile Building
a. GitHub - https://lnkd.in/g4r9naJ
b. LinkedIn - https://lnkd.in/g-KHHEC
c. Kaggle - https://lnkd.in/gBC77Hu
d. DS Resume - https://lnkd.in/gU8WVAF
🏅 10. Job Search
a. Daily Expert Tips & Advice - https://lnkd.in/g8z-xXD
---
Hope this helps! 👍
Updated on my site - https://www.claoudml.co/
  
  Here is a list of what I believe are the 10 Practical Steps for #DataScience:
1. Programming
a. Python - https://lnkd.in/gGQ7cuv
b. R - https://lnkd.in/giMGbph
c. SQL - https://lnkd.in/gM8nMNP
d. Command Line - https://lnkd.in/e3EQuis
2. Stats/Prob/Math
a. Coursera's Statistics w/ R - https://lnkd.in/gGT9NEf
b. edX's Probability - https://lnkd.in/gpUyC3P
c. Khan Academy Linear Algebra - https://lnkd.in/gMshbX4
3. Data Viz
a. Python Matplotlib- https://lnkd.in/gr3ifNt
b. R ggplot2 - https://lnkd.in/eThJXNr
4. Data Manipulation
a. Python Pandas - https://lnkd.in/g9kfpX4
b. R dplyr - https://lnkd.in/gAWusih
5. #MachineLearning
a. Google Crash Course - https://lnkd.in/gSgkVcT
b. Stanford Coursera - https://lnkd.in/g8ZG557
c. ISLR Book - https://lnkd.in/gk8GPZC
6. Experimental Design
a. Udacity A/B Testing - https://lnkd.in/gCerh4f
7. Business Sense
a. Metrics - https://lnkd.in/gZAG7bS
8. Communication
a. Storytelling - https://lnkd.in/gwjxVUu
9. Profile Building
a. GitHub - https://lnkd.in/g4r9naJ
b. LinkedIn - https://lnkd.in/g-KHHEC
c. Kaggle - https://lnkd.in/gBC77Hu
d. DS Resume - https://lnkd.in/gU8WVAF
🏅 10. Job Search
a. Daily Expert Tips & Advice - https://lnkd.in/g8z-xXD
---
Hope this helps! 👍
Updated on my site - https://www.claoudml.co/
lnkd.in
  
  LinkedIn
  This link will take you to a page that’s not on LinkedIn
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  Learning predictive analytic with python.pdf
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  deep_learning_adaptive_computation.pdf
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  chapter 5.pdf
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  #Automatic Interpretation of
Carotid Intima–Media
Thickness Videos Using
Convolutional Neural
Networks
#Chapter5 @Machine_learn
  Carotid Intima–Media
Thickness Videos Using
Convolutional Neural
Networks
#Chapter5 @Machine_learn
chapter 6.pdf
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  #Deep Cascaded Networks for
Sparsely Distributed Object
Detection from Medical
Images
#Chapter6 @Machine_learn
  Sparsely Distributed Object
Detection from Medical
Images
#Chapter6 @Machine_learn