AI/ML/DL/RL Starter Kit

AI/ML/DL/RL Starter Kit
please feel free to add your's

Our Official Blog
https://medium.com/machinelearningid

Free Machine
https://colab.research.google.com
@ihutagalung Coba Azure Machine Learning Studio tanpa perlu account Azure, login aja https://studio.azureml.net

Machine Learning
Basic concept of Machine Learning by Pakdhe Risman Adnan
https://www.dropbox.com/s/5lmqvo9fbs4w877/IntroML.pptx?dl=0

@ihutagalung
https://github.com/MSFTImagine/computerscience

@anthonyivan
https://github.com/josephmisiti/awesome-machine-learning

@welly_tambunan
- https://weltam.wordpress.com
- https://m.youtube.com/user/wellytambunan

@r_u_l_l_y
- buku machine learning nya Tom Mitchell
- Coursera machine learningnya Andrew Ng

@iarief
https://www.kaggle.com/c/titanic#tutorials

@anak10thn
https://wtf-deeplearning.github.io

@siganteng
Artificial Intelligence: A Modern Approach by Stuart Russel and Peter Norvig

@arrasy93
1. Buku Tom Mitchell
2. Buku Christopher Bishop
3. Probabilistiknya Machine Learning pake buku Hastie-Tibshirani sama David Barber
4. Papers
5. Ke bagian machine learning apapun yang anda mau tekuni NLP, RL, Vision, Unsupervised learning, etc.

Pakdhe Risman
1. Learning from Data tulisan Yasser Abu-Mustofa
2. Mainan SKLearn

@dkyhd
Introduction to information retrieval by Christoper D. Manning. Terutama yg suka dengan pengolahan teks.
https://nlp.stanford.edu/IR-book/

@imamdigmi
https://www.deeplearning.ai/

Deep Learning
Pakdhe Risman
Michael Nielsen http://neuralnetworksanddeeplearning.com

@arrasy93
https://www.youtube.com/watch?v=NfnWJUyUJYU

@TreeFPV
Ian Goodfellow http://www.deeplearningbook.org

@arynas04
http://www.wildml.com/2015/11/understanding-convolutional-neural-networks-for-nlp/
http://www.wildml.com/2015/12/implementing-a-cnn-for-text-classification-in-tensorflow/
https://medium.com/@arynas92/implementasi-cnn-untuk-klasifikasi-teks-menggunakan-tensorflow-3a720cc3afbc

@yhtwebid
https://www.datasciencecentral.com/profiles/blogs/free-deep-learning-book-mit-press
note, menurut Pakdhe Risman: Yoshua Bengio book. Comprehensive literature but not teaching style. Start with Michael Nielsen or Bishop first baru buku ini make sense.

Reinforcement Learning
@arrasy93
Reinforcement learning an introduction dari richard sutton dan andrew barto

Other must read book
@arrasy93
Bayesian Reasoning and Machine Learning David Barber (a life-changing book)

Learning Route
@arrasy93
review probs, stats, lin alg, sama numerical optimization -> ML
ways to become a data scientist
1. Have more domain knowledge on your problem
2. Have solid theoretical foundations to even further improve the models in datarobot
caveat: you need to improve your models and solid grasp on basics will help you more

@welly_tambunan @iarief
practical -> math

@iarief
as long as the person understands:
1. how to map the data he have into features
2. how to measure the accuracy of the model
3. bag of tricks to avoid overfitting
4. which approach works better when having a certain kind of data
he can build an useful model. it's ok to be a pragmatic data scientist

Pakdhe Risman
So far learning paling bagus itu read and code/solve problem. Baca buku yg tepat dan praktek problem solving. Dulu saya bacanya Learning from Data (Prof. Yasser), Pattern Recognition and Machine Learning (Prof. Bishop) dan The Element of Statistical Learning (Prof. Hestie). Setelah itu baru go deeper ke Deep Learning. Takes time but just enjoy the learning journey.

Math from Scratch
- Courses on khanacademy.org (Linear Algebra, Calculus, Statistic and probability)
- Linear Algebra: Step by Step by Kuldeep Singh
- Calculus Made Easy by S P Thompson

Python from Scratch
- Intro to Python for Data Science on datacamp.com
- https://youtube.com/playlist?list=PLQVvvaa0QuDfKTOs3Keq_kaG2P55YRn5v

Upcoming Events
https://machinelearningid.eventbrite.com

Sister Community
@machinelearninglombok
@semarangds
@computer_visionid

Sudah daftar di web DSI tapi belum diinvite di grup telegram? pm bang @Udhyn12

Literatures from past events
https://github.com/machineid/literatures

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