Agile Machine Learning.pdf
4.1 MB
Agile Machine Learning: Effective Machine Learning Inspired by the Agile Manifesto (2019)
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📌Free useful resources to learn Machine Learning
▪️Google
https://developers.google.com/machine-learning/crash-course
▪️Leetcode
https://leetcode.com/explore/featured/card/machine-learning-101
▪️Hackerrank
https://www.hackerrank.com/domains/ai/machine-learning
▪️FreeCodeCamp
https://www.freecodecamp.org/learn/machine-learning-with-python/
▪️Kaggle
https://www.kaggle.com/learn/intro-to-machine-learning
https://www.kaggle.com/learn/intermediate-machine-learning
▪️Geeksforgeeks
https://www.geeksforgeeks.org/machine-learning/
▪️Create ML Models
https://docs.microsoft.com/en-us/learn/paths/create-machine-learn-models/
▪️Machine Learning Test Cheat Sheet
https://www.cheatography.com/lulu-0012/cheat-sheets/test-ml/pdf/
🔻Learn from YouTube❗️
https://m.youtube.com/channel/UC2teOyP_yekDu9CPV3DvLPA
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https://developers.google.com/machine-learning/crash-course
▪️Leetcode
https://leetcode.com/explore/featured/card/machine-learning-101
▪️Hackerrank
https://www.hackerrank.com/domains/ai/machine-learning
▪️FreeCodeCamp
https://www.freecodecamp.org/learn/machine-learning-with-python/
▪️Kaggle
https://www.kaggle.com/learn/intro-to-machine-learning
https://www.kaggle.com/learn/intermediate-machine-learning
▪️Geeksforgeeks
https://www.geeksforgeeks.org/machine-learning/
▪️Create ML Models
https://docs.microsoft.com/en-us/learn/paths/create-machine-learn-models/
▪️Machine Learning Test Cheat Sheet
https://www.cheatography.com/lulu-0012/cheat-sheets/test-ml/pdf/
🔻Learn from YouTube❗️
https://m.youtube.com/channel/UC2teOyP_yekDu9CPV3DvLPA
➖➖➖➖➖➖➖➖➖➖➖➖➖➖
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Abdullah_Karasan_Machine_Learning_for_Financial_Risk_Management.pdf
3.6 MB
Abdullah Karasan - Machine Learning for Financial Risk Management with Python_ Algorithms for Modeling Risk-O'Reilly Media (2022).pdf
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🖥 Roadmap of free courses for learning Python and Machine learning.
▪Data Science
▪ AI/ML
▪ Web Dev
1. Start with this
https://kaggle.com/learn/python
2. Take any one of these
❯ https://openclassrooms.com/courses/6900856-learn-programming-with-python
❯ https://scaler.com/topics/course/python-for-beginners/
❯ https://simplilearn.com/learn-python-basics-free-course-skillup
3. Then take this
https://netacad.com/courses/programming/pcap-programming-essentials-python
4. Attempt for this certification
https://freecodecamp.org/learn/scientific-computing-with-python/
5. Take it to next level
❯ Data Scrapping, NumPy, Pandas
https://scaler.com/topics/course/python-for-data-science/
❯ Data Analysis
https://openclassrooms.com/courses/2304731-learn-python-basics-for-data-analysis
❯ Data Visualization
https://kaggle.com/learn/data-visualization
❯ Django
https://openclassrooms.com/courses/6967196-create-a-web-application-with-django
❯ Machine Learning
http://developers.google.com/machine-learning/crash-course
❯ Deep Learning (TensorFlow)
http://kaggle.com/learn/intro-to-deep-learning
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▪Data Science
▪ AI/ML
▪ Web Dev
1. Start with this
https://kaggle.com/learn/python
2. Take any one of these
❯ https://openclassrooms.com/courses/6900856-learn-programming-with-python
❯ https://scaler.com/topics/course/python-for-beginners/
❯ https://simplilearn.com/learn-python-basics-free-course-skillup
3. Then take this
https://netacad.com/courses/programming/pcap-programming-essentials-python
4. Attempt for this certification
https://freecodecamp.org/learn/scientific-computing-with-python/
5. Take it to next level
❯ Data Scrapping, NumPy, Pandas
https://scaler.com/topics/course/python-for-data-science/
❯ Data Analysis
https://openclassrooms.com/courses/2304731-learn-python-basics-for-data-analysis
❯ Data Visualization
https://kaggle.com/learn/data-visualization
❯ Django
https://openclassrooms.com/courses/6967196-create-a-web-application-with-django
❯ Machine Learning
http://developers.google.com/machine-learning/crash-course
❯ Deep Learning (TensorFlow)
http://kaggle.com/learn/intro-to-deep-learning
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Learning Ray [2023]Pumperla, Oakes, Liaw.pdf
7 MB
Learning Ray.
Flexible Distributed Python for Machine Learning. 2023
Max Pumperla,
Edward Oakes & Richard Liaw Foreword by Ion Stoica
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Flexible Distributed Python for Machine Learning. 2023
Max Pumperla,
Edward Oakes & Richard Liaw Foreword by Ion Stoica
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Forwarded from Jobs and Internships Updates
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For 2023, 2022 grads
Apply Link - https://tinyurl.com/39sy2ym3
Digitech Sols is hiring for the role of Data Entry/MIS Specialist.
Experience - 1 to 6 Years
Location - WFH
Apply Link - https://tinyurl.com/3e8mjsf3
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Machine Learning types
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Machine Learning & Data Science from Caltech
This is an introductory course in machine learning (ML) that covers the basic theory, algorithms, and applications. ML is a key technology in Big Data, and in many financial, medical, commercial, and scientific applications. It enables computational systems to adaptively improve their performance with experience accumulated from the observed data. ML has become one of the hottest fields of study today, taken up by undergraduate and graduate students from more than 20 different majors at Caltech. This course balances theory and practice, and covers the mathematical as well as the heuristic aspects.
⏰ Free Online Course
🎬 18 Video lessons
📁 downloadable resources
🏃♂️ Self paced
Offered by: Caltech
🔗 Course link
#Machine #Leaning #machinelearning #data_science
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This is an introductory course in machine learning (ML) that covers the basic theory, algorithms, and applications. ML is a key technology in Big Data, and in many financial, medical, commercial, and scientific applications. It enables computational systems to adaptively improve their performance with experience accumulated from the observed data. ML has become one of the hottest fields of study today, taken up by undergraduate and graduate students from more than 20 different majors at Caltech. This course balances theory and practice, and covers the mathematical as well as the heuristic aspects.
⏰ Free Online Course
🎬 18 Video lessons
📁 downloadable resources
🏃♂️ Self paced
Offered by: Caltech
🔗 Course link
#Machine #Leaning #machinelearning #data_science
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MIT machine learning course. Duration: 13 weeks.
Published: December 2020.
Type: open-source.
https://openlearninglibrary.mit.edu/courses/course-v1:MITx+6.036+1T2019/about
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Published: December 2020.
Type: open-source.
https://openlearninglibrary.mit.edu/courses/course-v1:MITx+6.036+1T2019/about
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Sebastian_Raschka_Vahid_Mirjalil.rar
182.5 MB
Python Machine Learning. Machine Learning and Deep Learning with Python, scikit-learn and TensorFlow [source code]
Author(s): Sebastian Raschka, Vahid Mirjalili
Publisher: Packt,
Year: 2017
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Author(s): Sebastian Raschka, Vahid Mirjalili
Publisher: Packt,
Year: 2017
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A recent survey shows that 9 out of 10 professionals struggle to switch to their desired companies, and on average, it takes 4-6 months to make a successful move.
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What you get:
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✅ 1:1 Mentorship from top industry experts from MAANG companies
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