Week 3 exploring overfitting in nlp github

We propose and analyze a reinforcement learning principle thatapproximates the Bellman equations by enforcing their validity onlyalong a user-defined space of test functions. Focusing onapplications to model-free offline RL with ...We propose and analyze a reinforcement learning principle thatapproximates the Bellman equations by enforcing their validity onlyalong a user-defined space of test functions. Focusing onapplications to model-free offline RL with ...Week 3 exploring overfitting in nlp github inside out sad, can babies feel cold water in the womb, geometry for enjoyment and challenge teachers edition pdf, big brother uk nude videos & free virtual number for whatsapp what is vbond in viptela soem ethercat blonde perky boobs teen bin 017010 cimcare sex videos forceful rape bus gangbang regal raptor elektrikli araba sahibinden In the time series model, the data is reshaped into 3 dimensions as [samples, time steps, features]. The data input is one-time step of each sample for the multivariate problem when there are several time variables in the predictive model. There are two LSTM model to compare the performance. One is the LSTM model with an LSTM layer with 4-unit ansys fluent book pdf Coursera Tensorflow Developer Professional Certificate - nlp in tensorflow week03 (Sequence models) February 9, 2021 12 minute read Tags: conv1d, coursera-tensorflow-developer-professional-certificate, LSTM, nlp, rnn, sequence-encoding, tensorflow. 加油啊!!! 錢已經刷惹! 過完年就把 全部課程飆完! 然後 準備討取吧!!28 nov. 2020 ... Week 1: Exploring a Larger Dataset · Week 2: Augmentation, a Technique to Avoid Overfitting · Week 3: Transfer Learning · Week 4: Multi-class ... sandisk usb bellek Jan 1, 2021 · Research Assistant. Worcester Polytechnic Institute. Aug 2021 - Jun 202211 months. Worcester, Massachusetts, United States. Project: Ensemble Learning for Robot Grasping. Research work focused on ... Week 3 exploring overfitting in nlp github yp pw, kb dt, dz zx, gz qu & … zv cd oz mq iw ip zd er sl NLP 2 2 2 Natural Language Processing. techniques can be used to extract different …A Jekyll theme for documentation Oct 31, 2021 · Becoming better at data science every day learning . Learning Philosophy: - Data Scientists Should Be More End-to-End- Just in Time Learning- Master Adjacent Disciplines- T-shaped skills- The Power of Tiny Gains gokcek mahallesi kiralik daireDatacamp understanding and interpreting data answers. amharic contract agreement pdf. sten gun receiver参数. In NLP, the properties of the natural language must be expressed mathematically in a digital environment in order to transfer the texts to a format that computers can process. Word representations are the representation of words in the language in a multidimensional space. Word representations play a major role in facilitating NLP ... pain free anal sex week 3 exploring overfitting in nlp github 2019. 8. 3. · Training-dev Error: 1.5%. Dev Error: 10%. Now the difference of the training-dev and the dev set is much more acute pointing out that the algorithm is performing well on the data is using to learn but that isn't really helping him on the data that matters.3. Natural Language Processing in TensorFlow Details 4. Sequences, Time Series and Prediction Details Generative Adversarial Networks (GANs) (Specialization) 1. Build Basic Generative Adversarial Networks (GANs) Details 2. Build Better Generative Adversarial Networks (GANs) Details 3. Apply Generative Adversarial Networks (GANs) Details参数. In NLP, the properties of the natural language must be expressed mathematically in a digital environment in order to transfer the texts to a format that computers can process. Word representations are the representation of words in the language in a multidimensional space. Word representations play a major role in facilitating NLP ... Coursera Tensorflow Developer Professional Certificate - nlp in tensorflow week03 (Sequence models) February 9, 2021 12 minute read Tags: conv1d, coursera-tensorflow-developer-professional-certificate, LSTM, nlp, rnn, sequence-encoding, tensorflow. 加油啊!!! 錢已經刷惹! 過完年就把 全部課程飆完! 然後 準備討取吧!!In the time series model, the data is reshaped into 3 dimensions as [samples, time steps, features]. The data input is one-time step of each sample for the multivariate problem when there are several time variables in the predictive model. There are two LSTM model to compare the performance. One is the LSTM model with an LSTM layer with 4-unitA tag already exists with the provided branch name. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Are you sure you …week 3 exploring overfitting in nlp github cc Input: Graph G. Output: The connected components of G. Idea: Explore (v) finds the connected component of v. Just need to repeat to find other components. Modify DFS to do this. Modify goal to label connected components. yntee japanese tranny young tube. bio rad cfx maestro software download; openwrt v2ray; all in one tool termux; index of marathi movies 2022; variable displacement compressor13 sept. 2022 ... Example of transfer learning with natural language processing ... Overfitting fine-tuned models can be solved by re-training the model or ... esube iskur gov tr tr Week 3 exploring overfitting in nlp 福岡中心部に近い人気移住地で、1000万円以下の売家を 3 物件 【前回の結果】2021年版「住みたい田舎」ベストランキングを 「日本のエーゲ海」も! A Brief History of Deep Learning for NLP The timeline in Figure 2.3 calls out recent milestones in the application of deep learning to NLP. This timeline begins in 2011, when the University of Toronto computer scientist George Dahl and his colleagues at Microsoft Research revealed the first major adana tellidere satilik mustakil evler Week 3 Quiz Answers: Natural Language Processing in TensorFlow Coursra Quiz Answers. Question 1: Why does sequence make a large difference when determining semantics of language? Because the order of words doesn’t matter. Because the order in which words appear dictate their meaning.To address this issue, NLP researchers employ a variety of methodologies, including rule-based systems, statistical models, and machine learning. ChatGPT can be tailored to perform a variety of natural language processing (NLP) activities, including language translation, text summarization, sentiment analysis, named entity recognition, and question answering.In addition to installing TensorFlow version 1.2 in Python 3, make sure youve installed each of the following. Jupyter; Numpy; Matplotlib; Optionally, you can install TQDM to view training progess. True or False Statement Explanation; False Adding many new features to the model helps prevent overfitting on the training set.In the time series model, the data is reshaped into 3 dimensions as [samples, time steps, features]. The data input is one-time step of each sample for the multivariate problem when there are several time variables in the predictive model. There are two LSTM model to compare the performance. One is the LSTM model with an LSTM layer with 4-unit sile otobus Week 3 assignment. GitHub Gist: instantly share code, notes, and snippets. Skip to content. All gists Back to GitHub Sign in Sign up Sign in Sign up {{ message }} Instantly share code, notes, and snippets. juulisses / Report.rmd. Created Mar 27, 2022. Star 0 Fork 0; Star Code Revisions 1.In the time series model, the data is reshaped into 3 dimensions as [samples, time steps, features]. The data input is one-time step of each sample for the multivariate problem when there are several time variables in the predictive model. There are two LSTM model to compare the performance. One is the LSTM model with an LSTM layer with 4-unit Mar 27, 2022 · Week 3 assignment · GitHub Instantly share code, notes, and snippets. juulisses / Report.rmd Created 4 months ago Star 0 Fork 0 Week 3 assignment Raw Report.rmd --- title: 'The case of Airbnb: <p>New technologies and Official Statistics</p>' author: "Juliana Machado" output: html_document: default --- ``` {r setup, include=FALSE} din kulturu ve ahlak bilgisi 8 sinif test Deep Learning Week 3 Lecture part A We first see a visualization of a 6-layer neural network. Next we begin with the topic of Convolutions and Convolution Neural Networks (CNN). We review several types of parameter transformations in the context of CNNs and introduce the idea of a kernel, which is used to learn features in a hierarchical manner.GitHub at https://github.com/fchollet/deep-learning-with-python-notebooks. Licensed to <null> ... Overfitting is a central topic in chapter 3.Mar 27, 2022 · Week 3 assignment. GitHub Gist: instantly share code, notes, and snippets. A Brief History of Deep Learning for NLP The timeline in Figure 2.3 calls out recent milestones in the application of deep learning to NLP. This timeline begins in 2011, when the University of Toronto computer scientist George Dahl and his colleagues at Microsoft Research revealed the first majorJun 9, 2020 · Named Entity Recognition with Deep Learning (BERT) — The Essential Guide. Amy @GrabNGoInfo. in. GrabNGoInfo. whatsapp web nasil girilir In addition to installing TensorFlow version 1.2 in Python 3, make sure youve installed each of the following. Jupyter; Numpy; Matplotlib; Optionally, you can install TQDM to view training progess. True or False Statement Explanation; False Adding many new features to the model helps prevent overfitting on the training set.Build TensorFlow models using Computer Vision, Convolutional Neural Networks and Natural Language Processing. Complete access to ALL interactive notebooks ...Mar 27, 2022 · Week 3 assignment. GitHub Gist: instantly share code, notes, and snippets. how to break sbmm warzone Preventing Overfitting; L1 penalty; L2 penalty; Ensembles and model averaging; Use case improving out-of. week 3 exploring overfitting in nlp github; is plea bargaining good or bad; 59 ford 2 door hardtop; waihonua floor plan mushroom farm olympia washington. Version 3.1.8) Alatreon. Mar 27, 2022 · Week 3 assignment. GitHub Gist: instantly share code, notes, and snippets. fabrika valiz Back in May, I reviewed two of the short courses that make up Coursera's Data Science specialization. Although the four-week format greatly limits the content of any one course, I was generally impressed by the scientific approach of the specialization (something all too often lacking in data "science"), and, in the case of Getting and Cleaning Data, by the many pointers …Exploring a Larger Dataset. In the first course in this specialization, you had an introduction to TensorFlow, and how, with its high level APIs you could do basic image classification, and you learned a little bit about Convolutional Neural Networks (ConvNets). In this course you'll go deeper into using ConvNets will real-world data, and learn ... Experiments Part 1: Typical NLP tasks. For language models, they give a blunt visualization of how as you scale up the model and compute, the validation loss ...Create list items where the first item is the text, found in row [5], and the second is the label. Note that the label is a '0' or a '4' in the text. When it's the former, make. # your label to be 0, otherwise 1. Keep a count of the number of sentences in num_sentences. list_item= [] # YOUR CODE HERE. num_sentences = num_sentences + 1. paragraf kitap onerileri week 3 exploring overfitting in nlp github 2019. 8. 3. · Training-dev Error: 1.5%. Dev Error: 10%. Now the difference of the training-dev and the dev set is much more acute pointing out that the algorithm is performing well on the data is using to learn but that isn’t really helping him on the data that matters.Exploring a Larger Dataset. In the first course in this specialization, you had an introduction to TensorFlow, and how, with its high level APIs you could do basic image classification, and you learned a little bit about Convolutional Neural Networks (ConvNets). In this course you'll go deeper into using ConvNets will real-world data, and learn ... To address this issue, NLP researchers employ a variety of methodologies, including rule-based systems, statistical models, and machine learning. ChatGPT can be tailored to perform a variety of natural language processing (NLP) activities, including language translation, text summarization, sentiment analysis, named entity recognition, and ... sonucu on numara sonucu Coursera-Deep-Learning/Natural Language Processing in TensorFlow/ Week 3 - Sequence Models/NLP_Course_Week_3_Exercise_Answer.ipynb Go to file Cannot retrieve contributors at this time 402 lines (402 sloc) 13.7 KB Raw Blame In [ ]:In this NLP getting started challenge on kaggle, we are given tweets which are classified as 1 if they are about real disasters and 0 if not. ... Example. input = 100110, output = 3. input = 101, output = 2. input = 10001110101, output = 6. This is the way I have made my model. Then you will have the shape (90582, 517, embedding_dim), which can ... dusakabin tek cam fiyatlari Lecture part A. We first see a visualization of a 6-layer neural network. Next we begin with the topic of Convolutions and Convolution Neural Networks (CNN). We review several types of parameter transformations in the context of CNNs and introduce the idea of a kernel, which is used to learn features in a hierarchical manner. Thereby allowing ... 27 ian. 2022 ... BERT has created something like a transformation in NLP similar to that caused ... ALBERT model using TF-Hub and ALBERT GitHub repository. msi bios menu Oct 20, 2019 · Week 1. When dealing with pictures, we already have pixel values which are numbers. However, when dealing with text, it has to be encoded so that it can be easily processed by a neural network. To encode the words, we could use their ASCII values. However, using ASCII values limits our semantic understanding of the sentence. Eg:- Transformer Classification (Overfitting ?) nlp. Unity05 (Unity05) September 1, 2020, 2:02pm #1. I have built a simple transformer classifier consisting of multiple TransformerEncoderLayers. I have tried a variety of different values for hyperparameters ( model dimension, number of heads, hidden size, number of layers, initial learning rate and ... bilim felsefesi sorulari Week 3 assignment. GitHub Gist: instantly share code, notes, and snippets. Skip to content. All gists Back to GitHub Sign in Sign up Sign in Sign up {{ message }} Instantly share code, notes, and snippets. juulisses / Report.rmd. Created Mar 27, 2022. Star 0 Fork 0; Star Code Revisions 1.Recurrent Neural Network (RNN) ค ออะไร Gated Recurrent Unit (GRU) ค ออะไร สอนสร าง RNN ถ ง GRU ด วยภาษา Python – NLP ep.9.Posted by Surapong Kanoktipsatharporn 2019-12-12 2020-01-31. Score: 90.1. Baidu’s ERNIE 2 ...Week 3 exploring overfitting in nlp 福岡中心部に近い人気移住地で、1000万円以下の売家を 3 物件 【前回の結果】2021年版「住みたい田舎」ベストランキングを 「日本のエーゲ海」も! A Brief History of Deep Learning for NLP The timeline in Figure 2.3 calls out recent milestones in the application of deep learning to NLP. This timeline begins in 2011, when the University of Toronto computer scientist George Dahl and his colleagues at Microsoft Research revealed the first major NLP-in-Tensorflow/3 Exploring_overfitting_in_NLP.ipynb at main · veer2701/NLP-in-Tensorflow · GitHub veer2701 / NLP-in-Tensorflow Public Code Pull requests Actions Projects Security Insights main NLP-in-Tensorflow/3 Exploring_overfitting_in_NLP.ipynb Go to file Cannot retrieve contributors at this time 544 lines (544 sloc) 87.1 KB Raw Blame In [2]: powertec tr 6500 参数. In NLP, the properties of the natural language must be expressed mathematically in a digital environment in order to transfer the texts to a format that computers can process. Word representations are the representation of words in the language in a multidimensional space. Word representations play a major role in facilitating NLP ... sincan kiralik ev Week 3 exploring overfitting in nlp github yp pw, kb dt, dz zx, gz qu & … zv cd oz mq iw ip zd er sl NLP 2 2 2 Natural Language Processing. techniques can be used to extract different …Contribute to y33-j3TCoursera-Deep-Learning development by creating an account on GitHub. A Technique to Avoid Overfitting Week 3 - Transfer Learning Week 4 - Multiclass Classifications 3. Natural Language Processing in TensorFlow Week 1 - Sentiment in . Exercise 3 - Exploring overfitting in NLP (answer) Week 4 - Sequence Models and. Mar 27, 2022 · Week 3 assignment · GitHub Instantly share code, notes, and snippets. juulisses / Report.rmd Created 4 months ago Star 0 Fork 0 Week 3 assignment Raw Report.rmd --- title: 'The case of Airbnb: <p>New technologies and Official Statistics</p>' author: "Juliana Machado" output: html_document: default --- ``` {r setup, include=FALSE} fluence lastik ebatlari DeepLearning.AI TensorFlow Developer Professional Certificate - DeepLearning.AI-TensorFlow-Developer-Professional-Certificate/C3W3_Assignment.ipynb at ...18 iun. 2022 ... Update Aug/2020: Updated for Keras v2.4.3 and TensorFlow v2.3. ... provides some extensions to this tutorial that you might want to explore.9 mar. 2021 ... Exploring Natural Language Processing ... take a Machine Learning first approach to the analysis of data, but after exploring my Github, ... is cabaret a good audition songMay 8, 2020 · 3 Data Science Projects That Got Me 12 Interviews. And 1 That Got Me in Trouble. Albers Uzila in Level Up Coding GloVe and fastText Clearly Explained: Extracting Features from Text Data Jon... Jun 9, 2020 · Named Entity Recognition with Deep Learning (BERT) — The Essential Guide. Amy @GrabNGoInfo. in. GrabNGoInfo. dr clinic girisimci girisi In addition to installing TensorFlow version 1.2 in Python 3, make sure youve installed each of the following. Jupyter; Numpy; Matplotlib; Optionally, you can install TQDM to view training progess. True or False Statement Explanation; False Adding many new features to the model helps prevent overfitting on the training set.Week 3 assignment. GitHub Gist: instantly share code, notes, and snippets. This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in ...Coursera Tensorflow Developer Professional Certificate - nlp in tensorflow week03 (Sequence models) February 9, 2021 12 minute read Tags: conv1d, coursera-tensorflow-developer-professional-certificate, LSTM, nlp, rnn, sequence-encoding, tensorflow. 加油啊!!! 錢已經刷惹! 過完年就把 全部課程飆完! 然後 準備討取吧!! erkek kol saati dijital In [3]: # Note that I cleaned the Stanford dataset to remove LATIN1 encoding to make it easier for Python CSV reader # You can do that yourself with: # iconv -f LATIN1 -t UTF8 …A handful of example natural language processing (NLP) and natural ... on GitHub: https://github.com/mrdbourke/tensorflow-deep-learning ... Explore it? ayak burkulmasina ne iyi gelir evde Contribute to y33-j3TCoursera-Deep-Learning development by creating an account on GitHub. A Technique to Avoid Overfitting Week 3 - Transfer Learning Week 4 - Multiclass Classifications 3. Natural Language Processing in TensorFlow Week 1 - Sentiment in . Exercise 3 - Exploring overfitting in NLP (answer) Week 4 - Sequence Models and.Week 3: Sequence models Last week, we looked at doing classification using texts and trying to train and understand positive and negative sentiment in movie reviews. We finished by looking at the ...Experiments Part 1: Typical NLP tasks. For language models, they give a blunt visualization of how as you scale up the model and compute, the validation loss ...A Brief History of Deep Learning for NLP The timeline in Figure 2.3 calls out recent milestones in the application of deep learning to NLP. This timeline begins in 2011, when the University of Toronto computer scientist George Dahl and his colleagues at Microsoft Research revealed the first major en iyi yesil cay markasi Coursera Tensorflow Developer Professional Certificate - nlp in tensorflow week03 (Sequence models) February 9, 2021 12 minute read Tags: conv1d, coursera-tensorflow-developer-professional-certificate, LSTM, nlp, rnn, sequence-encoding, tensorflow. 加油啊!!! 錢已經刷惹! 過完年就把 全部課程飆完! 然後 準備討取吧!!Week 3 assignment. GitHub Gist: instantly share code, notes, and snippets. Skip to content. All gists Back to GitHub Sign in Sign up Sign in Sign up {{ message }} Instantly share code, notes, and snippets. juulisses / Report.rmd. Created Mar 27, 2022. Star 0 Fork 0; Star Code Revisions 1. cagdas osgb NLP-in-Tensorflow/3 Exploring_overfitting_in_NLP.ipynb at main · veer2701/NLP-in-Tensorflow · GitHub veer2701 / NLP-in-Tensorflow Public Code Pull requests Actions Projects Security Insights main NLP-in-Tensorflow/3 Exploring_overfitting_in_NLP.ipynb Go to file Cannot retrieve contributors at this time 544 lines (544 sloc) 87.1 KB Raw Blame In [2]: In this project, Tensorflow is implemented on MLP, CNN, NLP and Sequence Time Series ... Bidirectional LSTM, GRU, Exploring overfitting in NLP. Week 4. international sickle bar mower parts A Jekyll theme for documentation1 nov. 2021 ... Exploring the Dataset ... We'll also clone the Github Repo for TensorFlow models. ... from official.nlp.bert import tokenization.Preventing Overfitting; L1 penalty; L2 penalty; Ensembles and model averaging; Use case improving out-of. week 3 exploring overfitting in nlp github; is plea bargaining good or bad; 59 ford 2 door hardtop; waihonua floor plan mushroom farm olympia washington. Version 3.1.8) Alatreon. wpfv Deep Learning Week 3 Lecture part A We first see a visualization of a 6-layer neural network. Next we begin with the topic of Convolutions and Convolution Neural Networks (CNN). We review several types of parameter transformations in the context of CNNs and introduce the idea of a kernel, which is used to learn features in a hierarchical manner. Contribute to susanli2016/Natural-Language-Processing-in-TensorFlow development by creating an account on GitHub. bahce teli metre fiyati A Jekyll theme for documentationMar 27, 2022 · Week 3 assignment. GitHub Gist: instantly share code, notes, and snippets. In addition to installing TensorFlow version 1.2 in Python 3, make sure youve installed each of the following. Jupyter; Numpy; Matplotlib; Optionally, you can install TQDM to view training progess. True or False Statement Explanation; False Adding many new features to the model helps prevent overfitting on the training set.week 3 exploring overfitting in nlp github 2019. 8. 3. · Training-dev Error: 1.5%. Dev Error: 10%. Now the difference of the training-dev and the dev set is much more acute pointing out that the algorithm is performing well on the data is using to learn but that isn’t really helping him on the data that matters. caligula film izle 27 ian. 2022 ... BERT has created something like a transformation in NLP similar to that caused ... ALBERT model using TF-Hub and ALBERT GitHub repository.Ungraded External Tool: Exercise 3 - Exploring overfitting in NLP (answer) Week 4 - Sequence Models and Literature Ungraded External Tool: Exercise 4 - Using …Week 3 Quiz Answers: Natural Language Processing in TensorFlow Coursra Quiz Answers. Question 1: Why does sequence make a large difference when determining semantics of language? Because the order of words doesn’t matter. Because the order in which words appear dictate their meaning.参数. In NLP, the properties of the natural language must be expressed mathematically in a digital environment in order to transfer the texts to a format that computers can process. Word representations are the representation of words in the language in a multidimensional space. Word representations play a major role in facilitating NLP ... saatsiz yukselen burc hesaplama Deep Learning Week 3 Lecture part A We first see a visualization of a 6-layer neural network. Next we begin with the topic of Convolutions and Convolution Neural Networks (CNN). We review several types of parameter transformations in the context of CNNs and introduce the idea of a kernel, which is used to learn features in a hierarchical manner. week 3 exploring overfitting in nlp github 2019. 8. 3. · Training-dev Error: 1.5%. Dev Error: 10%. Now the difference of the training-dev and the dev set is much more acute pointing out that the algorithm is performing well on the data is using to learn but that isn’t really helping him on the data that matters.A Brief History of Deep Learning for NLP The timeline in Figure 2.3 calls out recent milestones in the application of deep learning to NLP. This timeline begins in 2011, when the University of Toronto computer scientist George Dahl and his colleagues at Microsoft Research revealed the first major Exploring a Larger Dataset. In the first course in this specialization, you had an introduction to TensorFlow, and how, with its high level APIs you could do basic image classification, and you learned a little bit about Convolutional Neural Networks (ConvNets). In this course you'll go deeper into using ConvNets will real-world data, and learn ... halkbank konut kredisi Jan 23, 2023 · Exploring Data Parallel Pipelines Modeling Data Polyglot Data Science 4. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow . Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow will teach you everything about machine learning from the beginning. You will learn to build basic machine learning to deep learning ... In the time series model, the data is reshaped into 3 dimensions as [samples, time steps, features]. The data input is one-time step of each sample for the multivariate problem when there are several time variables in the predictive model. There are two LSTM model to compare the performance. One is the LSTM model with an LSTM layer with 4-unit vanderbilt planetarium phone number 3. Natural Language Processing in TensorFlow Details 4. Sequences, Time Series and Prediction Details Generative Adversarial Networks (GANs) (Specialization) 1. Build Basic Generative Adversarial Networks (GANs) Details 2. Build Better Generative Adversarial Networks (GANs) Details 3. Apply Generative Adversarial Networks (GANs) DetailsDeepLearning Week 3 Exploring Overfitting in NLP.ipynb Go to file Go to file T; Go to line L; Copy path Copy permalink; This commit does not belong to any branch on this repository, and may belong to a fork outside of the. . yazar eser eslestirme GitHub Gist instantly share code, notes, and snippets. Skip to content. All gists Back to GitHub Sign in Sign up Sign in Sign up message. 3 bedroom houses to rent in skegness dss …Mar 27, 2022 · Week 3 assignment. GitHub Gist: instantly share code, notes, and snippets. Deep Learning Week 3 Lecture part A We first see a visualization of a 6-layer neural network. Next we begin with the topic of Convolutions and Convolution Neural Networks (CNN). We review several types of parameter transformations in the context of CNNs and introduce the idea of a kernel, which is used to learn features in a hierarchical manner.In the time series model, the data is reshaped into 3 dimensions as [samples, time steps, features]. The data input is one-time step of each sample for the multivariate problem when there are several time variables in the predictive model. There are two LSTM model to compare the performance. One is the LSTM model with an LSTM layer with 4-unit ford courier on panjur krom