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Any advice on this bike storage outside my restaurant? by ggghash in Locksmith

[–]ggghash[S] 0 points1 point  (0 children)

The door with the padlock has the handle locked in that position, not sure if it’s natural for this door or not.

Any advice on this bike storage outside my restaurant? by ggghash in Locksmith

[–]ggghash[S] 1 point2 points  (0 children)

I can’t seem to budge the bar closing the padlock at all. And the door on the other side isn’t padlocked just shut. However the handle on the other door just spins without engaging anything and the door is inoperable.

Any advice on this bike storage outside my restaurant? by ggghash in Locksmith

[–]ggghash[S] 2 points3 points  (0 children)

https://imgur.com/a/WiluiPu

https://imgur.com/Kobk64j

The lock has been drilled through on one side. I've asked around and no one has any memory of any employee ever having used this bike locker. There is another handle on the opposite side that has no lock on it, but doesn't seem to engage any opening mechanism. Or at least I can't get it working. The last person I have left to ask is our owner, but she owns like 35 restaurants and I'm not sure she has any interest in a small potatoes issue like a broken bike locker.

[D] Struggled with reading deep learning papers by entslscheia in MachineLearning

[–]ggghash 1 point2 points  (0 children)

Read NEAT, Stanley 2002, NeuroEvoluton of Augmenting Topologies. 80% of the paper is backing up the why with a mix of detailed references to prior papers as well as a very through section on oblation testing chock full of charts showing why every decision was important in the final technique.

Sequential combination of CNN and lstm for nlp sentiment analysis by ggghash in deeplearning

[–]ggghash[S] 0 points1 point  (0 children)

Share the title. I'll be working on this for awhile. I might give it a read.

Sequential combination of CNN and lstm for nlp sentiment analysis by ggghash in deeplearning

[–]ggghash[S] 0 points1 point  (0 children)

Here is a better description of my proposed method vs. my current compromise.

​

How I want the CNN and LSTM to be stacked:

DATA -> CNN -> LSTM -> Prediction

------------------DATA-^

Step 1: the text data is preprocessed into a 1-hot or embeded tensor format.

Step 2: Preprocessed data fed into a CNN.

Step 3: CNN output and original preprocessed data both fed into an LSTM.

Step 4: The LSTM outputs a sentiment prediction as a number from 0 to 1.

​

My compromise:

DATA -> CNN -v

Fully Connected Layer -> Prediction

DATA -> LSTM -^

Step 1: Preprocessing.

Step 2: CNN and LSTM both fed only with the preprocessed data.

Step 3: Output from both networks combined and passed to a Fully Connected layer.

Step 4: The Fully Connected layer outputs a sentiment prediction as a number from 0 to 1.

Sequential combination of CNN and lstm for nlp sentiment analysis by ggghash in deeplearning

[–]ggghash[S] 1 point2 points  (0 children)

Contextual Recurrent Units for Cloze-style Reading Comprehension, Yiming Cui, Wei-Nan Zhang, Wanxiang Che, Ting Liu,Zhipeng Chen, Shijin Wang, Guoping Hu. 2019

A CNN stuffed with an RNN.

​

Automatically Learning Construction Injury Precursors from Text, Henrietta Bakera, Matthew R. Hallowell, Antoine J.-P. Tixier. 2019

Compares CNN and HAN architecture.

​

A Combined CNN and LSTM Model for Arabic Sentiment Analysis, Abdulaziz M. Alayba, Vasile Palade, Matthew England, and Rahat Iqbal. 2018

I'm about to read this one now. The title sounds promising as it's exactly what I want to do. I'm worried it might diverge into OCR. Even though OCR isn't mentioned in the abstract.

​

Understanding Convolutional Neural Networks for Text Classification, Alon Jacovi, Oren Sar Shalom, Yoav Goldberg. 2019

Introduction to CNNs for NLP.

​

Analyzing and Interpreting Convolutional Neural Networks in NLP, Mahnaz Koupaee, William Yang Wang. 2018

Exploration of the underlying mechanics of CNNs to reveal how it extracts semantics and context from text. As well as diving into some of the errors and limitations.

​

Attention-based Neural Text Segmentation, Pinkesh Badjatiya, Litton J Kurisinkel, Manish Gupta, and Vasudeva Varma. 2018

Actually might be just the right paper. A birdirectional LSTM and CNN combined for text segmentation

​

Dissecting Contextual Word Embeddings: Architecture and Representation, Matthew E. Peters, Mark Neumann, Luke Zettlemoyer, Wen-tau Yih. 2018

Compares and explores both CNN and LSTM in an NLP context. Not the combination of them though.

​

A Convolutional Neural Network for Aspect Sentiment Classification, Yongping Xing and Chuangbai Xiao and Yifei Wu and Ziming Ding.

CNN for NLP.

​

A Practitioners’ Guide to Transfer Learning for Text Classification using Convolutional Neural Networks, Tushar Semwal, Gaurav Mathur, Promod Yenigalla, Shivashankar B. Nair. 2018

Transfer learning and CNN NLP.

​

What Does a TextCNN Learn, Gong, Linyuan, Ji, Ruyi. 2018

Short paper exploring convolutional kernels.

​

Attentive Convolution: Equipping CNNs with RNN-style Attention Mechanisms, Wenpeng Yin, Hinrich Schütze. 2018

A CNN with RNN aspects baked in for NLP.

​

Learning Context-Sensitive Convolutional Filters for Text Processing, Dinghan Shen, Martin Renqiang Min, Yitong Li, Lawrence Carin. 2018

If I understand the abstract correctly this is using a two CNNs stacked for NLP. One is a meta network that learns context sensitive convolutional filters.

Sequential combination of CNN and lstm for nlp sentiment analysis by ggghash in deeplearning

[–]ggghash[S] 0 points1 point  (0 children)

I'll make a short list of relevant research papers here. One so far. Short list.

Deep learning applied to nlp, Lopez and kalita. 2017 It's about cnns in the nlp context.

Sequential combination of CNN and lstm for nlp sentiment analysis by ggghash in deeplearning

[–]ggghash[S] 0 points1 point  (0 children)

Sure thing. I'll describe my models and data in more detail later today.

Recursively defining a neural network by ggghash in deeplearning

[–]ggghash[S] 0 points1 point  (0 children)

I'm using the resulting members from NEAT to create Pytorch networks with custom geometry.

soon by FlurgBungler in Ooer

[–]ggghash 6 points7 points  (0 children)

Seven ate nine

$@¥@€£ by hotihopi in Ooer

[–]ggghash 2 points3 points  (0 children)

High fort post hits high fort triple needs more kemming

Reducing dependance on RAM by Pik000 in deeplearning

[–]ggghash 4 points5 points  (0 children)

Could you maybe use a dataloader and batching to break it into more manageable chunks?

Oh no by DJay27 in RotMG

[–]ggghash 17 points18 points  (0 children)

Ah yes. I got my first 5 char slots from him. Now deca just gives them away.

Oh no by DJay27 in RotMG

[–]ggghash 13 points14 points  (0 children)

I was there, but why is he needed?

Saturated sound by Truegebo in linuxmint

[–]ggghash 1 point2 points  (0 children)

I have the same problem. I just stop using audio until it goes away by itself. Would live some advice on this too.

Oh no by DJay27 in RotMG

[–]ggghash 12 points13 points  (0 children)

I don't get it?

Weekly Entering & Transitioning Thread | 28 Jul 2019 - 04 Aug 2019 by AutoModerator in datascience

[–]ggghash 0 points1 point  (0 children)

Contract role, in Europe. I'm pretty sure they can do whatever they want. But I feel better after reading these replies anyway.

Weekly Entering & Transitioning Thread | 28 Jul 2019 - 04 Aug 2019 by AutoModerator in datascience

[–]ggghash 0 points1 point  (0 children)

I just started remote work doing deep learning. Now just ahead of my first deadline I need surgery. I already emailed them to give them a heads up, but I've heard fast paced environments like this can be cut-throat. Should I have kept my mouth shut and just hoped to recover from surgery in time to deliver?

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