#معرفی_کتاب
Hands-On Machine Learning with Scikit-Learn and TensorFlow
https://opensource.com/article/17/4/book-review-hands-machine-learning-scikit-learn-tensorflow
#book #deep_learning #machine_learning #Tensorflow #scikit_learn
Hands-On Machine Learning with Scikit-Learn and TensorFlow
https://opensource.com/article/17/4/book-review-hands-machine-learning-scikit-learn-tensorflow
#book #deep_learning #machine_learning #Tensorflow #scikit_learn
Opensource.com
Book review: Hands-On Machine Learning with Scikit-Learn and TensorFlow
Get started with machine learning with the book, Hands-On Machine Learning with Scikit-Learn and TensorFlow by Aurélien Géron, which uses production-ready Python frameworks and provides an example end-to-end machine learning project.
#کورس،
❌متاسفانه این دوره رایگان نیست
Applied Data Science with #Python Specialization
(Upcoming session: Jul 3 — Aug 7 , 2017)
http://bit.ly/2rZeVxj
#pandas, #matplotlib, #scikit_learn, #nltk
❌متاسفانه این دوره رایگان نیست
Applied Data Science with #Python Specialization
(Upcoming session: Jul 3 — Aug 7 , 2017)
http://bit.ly/2rZeVxj
#pandas, #matplotlib, #scikit_learn, #nltk
#خبر، #twitter
What ML stack do tech startups use, you ask? Let's look at the Hacker News jobs board.
https://twitter.com/fchollet/status/961294612466868224
Out of 964 job postings:
- 12 posts mention #TensorFlow
- 7 #Keras
- 5 #Scikit-Learn
- 1 #Caffe
- 0 #PyTorch, #MXNet
Also note that:
- 89 posts mention ML (9%)
- 34 AI
- 18 deep learning
What ML stack do tech startups use, you ask? Let's look at the Hacker News jobs board.
https://twitter.com/fchollet/status/961294612466868224
Out of 964 job postings:
- 12 posts mention #TensorFlow
- 7 #Keras
- 5 #Scikit-Learn
- 1 #Caffe
- 0 #PyTorch, #MXNet
Also note that:
- 89 posts mention ML (9%)
- 34 AI
- 18 deep learning
Twitter
François Chollet
What ML stack do tech startups use, you ask? Let's look at the Hacker News jobs board. Out of 964 job postings: - 12 posts mention TensorFlow - 7 Keras - 5 Scikit-Learn - 1 Caffe - 0 PyTorch, MXNet Also note that: - 89 posts mention ML (9%) - 34 AI - 18 deep…
#آموزش #سورس_کد
Implementation of research papers on Deep Learning+ NLP+ CV in Python using #Keras, #Tensorflow and #Scikit_Learn.
http://deeplearn-ai.com
[1] Correlation Neural Networks. CV, transfer learning, representation learning.
[2] Reasoning With Neural Tensor Networks for Knowledge Base Completion. NLP, ML.
[3] Common Representation Learning Using Step-based Correlation Multi-Modal CNN. CV, transfer learning, representation learning.
[4] ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs. NLP, deep learning, sentence matching.
[5] Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks. NLP, deep learning, CQA.
[6] Combining Neural, Statistical and External Features for Fake News Stance Identification. NLP, IR, deep learning.
[7] WIKIQA: A Challenge Dataset for Open-Domain Question Answering. NLP, deep learning, CQA.
[8] Siamese Recurrent Architectures for Learning Sentence Similarity. NLP, sentence similarity, deep learning.
[9] Convolutional Neural Tensor Network Architecture for Community Question Answering. NLP, deep learning, CQA.
[10] Map-Reduce for Machine Learning on Multicore. map-reduce, hadoop, ML.
[11] Teaching Machines to Read and Comprehend. NLP, deep learning.
[12] Improved Representation Learning for Question Answer Matching. NLP, deep learning, CQA.
[13] External features for community question answering. NLP, deep learning, CQA.
[14] Language Identification and Disambiguation in Indian Mixed-Script. NLP, IR, ML.
[15] Construction of a Semi-Automated model for FAQ Retrieval via Short Message Service. NLP, IR, ML.
🔗https://github.com/GauravBh1010tt/DeepLearn
#deep_learning #nlp #vision
Implementation of research papers on Deep Learning+ NLP+ CV in Python using #Keras, #Tensorflow and #Scikit_Learn.
http://deeplearn-ai.com
[1] Correlation Neural Networks. CV, transfer learning, representation learning.
[2] Reasoning With Neural Tensor Networks for Knowledge Base Completion. NLP, ML.
[3] Common Representation Learning Using Step-based Correlation Multi-Modal CNN. CV, transfer learning, representation learning.
[4] ABCNN: Attention-Based Convolutional Neural Network for Modeling Sentence Pairs. NLP, deep learning, sentence matching.
[5] Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks. NLP, deep learning, CQA.
[6] Combining Neural, Statistical and External Features for Fake News Stance Identification. NLP, IR, deep learning.
[7] WIKIQA: A Challenge Dataset for Open-Domain Question Answering. NLP, deep learning, CQA.
[8] Siamese Recurrent Architectures for Learning Sentence Similarity. NLP, sentence similarity, deep learning.
[9] Convolutional Neural Tensor Network Architecture for Community Question Answering. NLP, deep learning, CQA.
[10] Map-Reduce for Machine Learning on Multicore. map-reduce, hadoop, ML.
[11] Teaching Machines to Read and Comprehend. NLP, deep learning.
[12] Improved Representation Learning for Question Answer Matching. NLP, deep learning, CQA.
[13] External features for community question answering. NLP, deep learning, CQA.
[14] Language Identification and Disambiguation in Indian Mixed-Script. NLP, IR, ML.
[15] Construction of a Semi-Automated model for FAQ Retrieval via Short Message Service. NLP, IR, ML.
🔗https://github.com/GauravBh1010tt/DeepLearn
#deep_learning #nlp #vision
GitHub
GitHub - GauravBh1010tt/DeepLearn: Implementation of research papers on Deep Learning+ NLP+ CV in Python using Keras, Tensorflow…
Implementation of research papers on Deep Learning+ NLP+ CV in Python using Keras, Tensorflow and Scikit Learn. - GitHub - GauravBh1010tt/DeepLearn: Implementation of research papers on Deep Learni...
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Interactive SVM Explorer, using Dash and scikit-learn
https://github.com/plotly/dash-svm
#SVM #Plotly #scikit_learn
https://github.com/plotly/dash-svm
#SVM #Plotly #scikit_learn
#کورس #ویدیو
معرفی کورس جبرخطی عددی برای برنامه نویسان
Computational Linear Algebra for Coders
این کورس در سال ۲۰۱۷ در دانشگاه San Francisco توسط Rachel Thomas تدریس شد.
Rachel Thomas
دکترای ریاضی دارند و به همراه jeremy howard ,
Fast.ai
رو ایجاد کردند.
course review:
https://machinelearningmastery.com/computational-linear-algebra-coders-review/
کتاب آنلاین:
https://github.com/fastai/numerical-linear-algebra/blob/master/README.md
ویدیوها:
https://www.youtube.com/playlist?list=PLtmWHNX-gukIc92m1K0P6bIOnZb-mg0hY
The course uses #Python with examples using #NumPy, #scikit_learn, #numba, #pytorch, and more.
Course Contests
0. Course Logistics
1. Why are we here?
2. Topic Modeling with NMF and SVD
3. Background Removal with Robust PCA
4. Compressed Sensing with Robust Regression
5. Predicting Health Outcomes with Linear Regressions
6. How to Implement Linear Regression
7. PageRank with Eigen Decompositions
8. Implementing QR Factorization
معرفی کورس جبرخطی عددی برای برنامه نویسان
Computational Linear Algebra for Coders
این کورس در سال ۲۰۱۷ در دانشگاه San Francisco توسط Rachel Thomas تدریس شد.
Rachel Thomas
دکترای ریاضی دارند و به همراه jeremy howard ,
Fast.ai
رو ایجاد کردند.
course review:
https://machinelearningmastery.com/computational-linear-algebra-coders-review/
کتاب آنلاین:
https://github.com/fastai/numerical-linear-algebra/blob/master/README.md
ویدیوها:
https://www.youtube.com/playlist?list=PLtmWHNX-gukIc92m1K0P6bIOnZb-mg0hY
The course uses #Python with examples using #NumPy, #scikit_learn, #numba, #pytorch, and more.
Course Contests
0. Course Logistics
1. Why are we here?
2. Topic Modeling with NMF and SVD
3. Background Removal with Robust PCA
4. Compressed Sensing with Robust Regression
5. Predicting Health Outcomes with Linear Regressions
6. How to Implement Linear Regression
7. PageRank with Eigen Decompositions
8. Implementing QR Factorization
MachineLearningMastery.com
Computational Linear Algebra for Coders Review - MachineLearningMastery.com
Numerical linear algebra is concerned with the practical implications of implementing and executing matrix operations in computers with real data.
It is an area that requires some previous experience of linear algebra and is focused on both the performance…
It is an area that requires some previous experience of linear algebra and is focused on both the performance…