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How Machine Learning is Changing e-Government @Machine_learn
tf.keras.Model
https://www.tensorflow.org/api_docs/python/tf/keras/Model
Code: https://github.com/tensorflow/tensorflow/blob/v2.4.1/tensorflow/python/keras/engine/training.py#L138-L2675
@Machine_learn
https://www.tensorflow.org/api_docs/python/tf/keras/Model
Code: https://github.com/tensorflow/tensorflow/blob/v2.4.1/tensorflow/python/keras/engine/training.py#L138-L2675
@Machine_learn
TensorFlow
tf.keras.Model | TensorFlow v2.16.1
A model grouping layers into an object with training/inference features.
با عرض سلام ما پكيج ٣٦ پروژه عملي با يادگيري عميق همراه با داكيومنت فارسي را براي دوستاني كه مي خواهند در اين حوزه به صورت عملي كار كنند تهيه كرديم سرفصل هاي اين پكيج به ترتيب زير مي باشند:
1-Deep Learning Basic
-01_Introduction
--01_How_TensorFlow_Works
--02_Creating_and_Using_Tensors
--03_Implementing_Activation_Functions
-02_TensorFlow_Way
--01_Operations_as_a_Computational_Graph
--02_Implementing_Loss_Functions
--03_Implementing_Back_Propagation
--04_Working_with_Batch_and_Stochastic_Training
--05_Evaluating_Models
-03_Linear_Regression
--linear regression
--Logistic Regression
-04_Neural_Networks
--01_Introduction
--02_Single_Hidden_Layer_Network
--03_Using_Multiple_Layers
-05_Convolutional_Neural_Networks
--Convolution Neural Networks
--Convolutional Neural Networks Tensorflow
--TFRecord For Deep learning Models
-06_Recurrent_Neural_Networks
--Recurrent Neural Networks (RNN)
2-Classification apparel
-Classification apparel double capsule
-Classification apparel double cnn
3-ALZHEIMERS USING CNN(ResNet)
4-Fake News (Covid-19 dataset)
-Multi-channel
-3DCNN model
-Base line+ Char CNN
-Fake News Covid CapsuleNet
5-3DCNN Fake News
6-recommender systems
-GRU+LSTM MovieLens
7-Multi-Domain Sentiment Analysis
-Dranziera CapsuleNet
-Dranziera CNN Multi-channel
-Dranziera LSTM
8-Persian Multi-Domain SA
-Bi-GRU Capsule Net
-Multi-CNN
9-Recommendation system
-Factorization Recommender, Ranking Factorization Recommender, Item Similarity Recommender (turicreate)
-SVD, SVD++, NMF, Slope One, k-NN, Centered k-NN, k-NN Baseline, Co-Clustering(surprise)
10-NihX-Ray
-optimized CNN on FullDataset Nih-Xray
-MobileNet
-Transfer learning
-Capsule Network on FullDataset Nih-Xray
هزينه اين پكيج ٥٠٠هزار مي باشد و صرفا هزينه تهيه ديتاست هاست.
جهت خريد مي توانيد با ايدي بنده در ارتباط باشيد
@Raminmousa
1-Deep Learning Basic
-01_Introduction
--01_How_TensorFlow_Works
--02_Creating_and_Using_Tensors
--03_Implementing_Activation_Functions
-02_TensorFlow_Way
--01_Operations_as_a_Computational_Graph
--02_Implementing_Loss_Functions
--03_Implementing_Back_Propagation
--04_Working_with_Batch_and_Stochastic_Training
--05_Evaluating_Models
-03_Linear_Regression
--linear regression
--Logistic Regression
-04_Neural_Networks
--01_Introduction
--02_Single_Hidden_Layer_Network
--03_Using_Multiple_Layers
-05_Convolutional_Neural_Networks
--Convolution Neural Networks
--Convolutional Neural Networks Tensorflow
--TFRecord For Deep learning Models
-06_Recurrent_Neural_Networks
--Recurrent Neural Networks (RNN)
2-Classification apparel
-Classification apparel double capsule
-Classification apparel double cnn
3-ALZHEIMERS USING CNN(ResNet)
4-Fake News (Covid-19 dataset)
-Multi-channel
-3DCNN model
-Base line+ Char CNN
-Fake News Covid CapsuleNet
5-3DCNN Fake News
6-recommender systems
-GRU+LSTM MovieLens
7-Multi-Domain Sentiment Analysis
-Dranziera CapsuleNet
-Dranziera CNN Multi-channel
-Dranziera LSTM
8-Persian Multi-Domain SA
-Bi-GRU Capsule Net
-Multi-CNN
9-Recommendation system
-Factorization Recommender, Ranking Factorization Recommender, Item Similarity Recommender (turicreate)
-SVD, SVD++, NMF, Slope One, k-NN, Centered k-NN, k-NN Baseline, Co-Clustering(surprise)
10-NihX-Ray
-optimized CNN on FullDataset Nih-Xray
-MobileNet
-Transfer learning
-Capsule Network on FullDataset Nih-Xray
هزينه اين پكيج ٥٠٠هزار مي باشد و صرفا هزينه تهيه ديتاست هاست.
جهت خريد مي توانيد با ايدي بنده در ارتباط باشيد
@Raminmousa
Machine learning books and papers pinned «با عرض سلام ما پكيج ٣٦ پروژه عملي با يادگيري عميق همراه با داكيومنت فارسي را براي دوستاني كه مي خواهند در اين حوزه به صورت عملي كار كنند تهيه كرديم سرفصل هاي اين پكيج به ترتيب زير مي باشند: 1-Deep Learning Basic -01_Introduction --01_How_TensorFlow_Works…»
A Survey of Data Augmentation Approaches for NLP
Data Augmentation has becoming more and more popular and important task in NLP. On the contrary to Computer Vision where all methods now are well-known and already pre-implemented in libraries, in NLP the situation is not so consistent.
So, there has been published a nice paper that accumulated all known due today techniques, models and applications of data augmentation in texts:
https://arxiv.org/abs/2105.03075
In the appendix you can find the list of open-source that may be useful for your task.
@Machine_learn
Data Augmentation has becoming more and more popular and important task in NLP. On the contrary to Computer Vision where all methods now are well-known and already pre-implemented in libraries, in NLP the situation is not so consistent.
So, there has been published a nice paper that accumulated all known due today techniques, models and applications of data augmentation in texts:
https://arxiv.org/abs/2105.03075
In the appendix you can find the list of open-source that may be useful for your task.
@Machine_learn
ALIGN: Scaling Up Visual and Vision-Language Representation Learning With Noisy Text Supervision
http://ai.googleblog.com/2021/05/align-scaling-up-visual-and-vision.html
@Machine_learn
http://ai.googleblog.com/2021/05/align-scaling-up-visual-and-vision.html
@Machine_learn
research.google
ALIGN: Scaling Up Visual and Vision-Language Representation Learning With Noisy
Posted by Chao Jia and Yinfei Yang, Software Engineers, Google Research Learning good visual and vision-language representations is critical to sol...
500 + 𝗔𝗿𝘁𝗶𝗳𝗶𝗰𝗶𝗮𝗹 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝗰𝗲 𝗣𝗿𝗼𝗷𝗲𝗰𝘁 𝗟𝗶𝘀𝘁 𝘄𝗶𝘁𝗵 𝗰𝗼𝗱𝗲
https://github.com/ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code
@Machine_learn
https://github.com/ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code
@Machine_learn
GitHub
GitHub - ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code: 500 AI Machine learning Deep…
500 AI Machine learning Deep learning Computer vision NLP Projects with code - ashishpatel26/500-AI-Machine-learning-Deep-learning-Computer-vision-NLP-Projects-with-code
👍1
Project Guideline: Enabling Those with Low Vision to Run Independently
http://ai.googleblog.com/2021/05/project-guideline-enabling-those-with.html
@Machine_learn
http://ai.googleblog.com/2021/05/project-guideline-enabling-those-with.html
@Machine_learn
research.google
Project Guideline: Enabling Those with Low Vision to Run Independently
Posted by Xuan Yang, Software Engineer, Google Research For the 285 million people around the world living with blindness or low vision, exercising...
Topic : Sudoku solver (SolSudo)
Abstract : SolSudo is a Sudoku solver made using Deep Learning. SolSudo can solve sudokus using images. This has an intelligent solution method. According to this method, the model predicts the blank digits, and when each level is completed, the filled blanks are placed one after another. Each time a digit is filled, new sudoku will be fed to the solver to determine the next digit. Again and again, until there is no blank left. One of the features of this project is detecting sudoku from an image and filling in the blanks. This requires tesseract-ocr, however, which may cause problems. Therefore, I devised a method, in which the Sudoku numbers are entered one by one, and 0 is used for the empty spaces. Below is an example of Sudoku, its detection, and its solution.
Github Link : https://github.com/AryaKoureshi/SolSudo
Linkedin Link : https://www.linkedin.com/posts/arya-koureshi_deeplearning-python-tensorflow-activity-6711641409658716160-kdSD
@Machine_learn
Abstract : SolSudo is a Sudoku solver made using Deep Learning. SolSudo can solve sudokus using images. This has an intelligent solution method. According to this method, the model predicts the blank digits, and when each level is completed, the filled blanks are placed one after another. Each time a digit is filled, new sudoku will be fed to the solver to determine the next digit. Again and again, until there is no blank left. One of the features of this project is detecting sudoku from an image and filling in the blanks. This requires tesseract-ocr, however, which may cause problems. Therefore, I devised a method, in which the Sudoku numbers are entered one by one, and 0 is used for the empty spaces. Below is an example of Sudoku, its detection, and its solution.
Github Link : https://github.com/AryaKoureshi/SolSudo
Linkedin Link : https://www.linkedin.com/posts/arya-koureshi_deeplearning-python-tensorflow-activity-6711641409658716160-kdSD
@Machine_learn
Cicolani2021_Book_BeginningRoboticsWithRaspberry.pdf
7.3 MB
Beginning Robotics with Raspberry Pi and Arduino #2021 #book @Machine_learn
با عرض سلام دوستانی که نیاز به تهیه کتاب های زبان اصلی دارند می توانند با ارسال نام کتاب و ناشر آن به ایدی بنده ثبت سفارش کنند. تمامی کتاب ها با 50% تخفیف دلاری برای تمامی رشته ها قابل دسترس می باشد.
@Raminmousa
@Raminmousa
Machine learning books and papers pinned «با عرض سلام دوستانی که نیاز به تهیه کتاب های زبان اصلی دارند می توانند با ارسال نام کتاب و ناشر آن به ایدی بنده ثبت سفارش کنند. تمامی کتاب ها با 50% تخفیف دلاری برای تمامی رشته ها قابل دسترس می باشد. @Raminmousa»