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H: The robustness of the Frobenius and L2,1 norms to the outlier
I have a question about the properties of the Frobenius and L$_{2,1}$ norms. Why is the L$_{2,1}$ norm more robust to the outlier than the Frobenius norm?
PS: For a matrix $A\in\mathbb{R}^{n\times d}$, it can be easily seen that
$$
\text{Frobenius norm:}... |
H: How can I classify specific types of words in a document given I have the full text of the document and the labels
I am working on a project that involves picking out specific kinds of objects from text. The documents I am going though are life sciences and biomedical in nature, and in these documents there are spe... |
H: Is it mandatory to change the dtype='object' to 'category' before label encoding
I have seen some people change the datatype(from object to category) of the feature they want to encode.
AI: It depends on the approach you take for label encoding. If you want to use .cat.codes then you need to convert it into categor... |
H: Neural Network Optimization steps order
I have a very basic question on the optimization algotithm, when I'm adjusting weights and biases in a NN, should I:
Forward propagate and backpropagate to calculate gradient descent (DC) for each batch once and then repeat for iterations_number times.
or
Forward propagate... |
H: Representing the architecture of a deep CNN
Suppose I am feeding a $60\times60$ RGB image as the input to deep CNN with the first layer created using the following Keras code model.add(Conv2D(64, (3, 3), input_shape=(60, 60, 3))).
Will 64 filters be created for each channel (red, green and blue) of the image?
Is t... |
H: Can a trained recognition model be used to generate a sample?
Suppose we have trained a cat classification network. It takes in an image (as a vector) x and returns $\hat{y}\in(0,1)$. The loss function is the typical cross entropy function. Shouldn't it be possible to now perform gradient descent on the space of im... |
H: why do transformers mask at every layer instead of just at the input layer?
working thru the annotated transformer, I see that every layer in both the encoder (mask paddings) and decoder (mask padding + future positions) get masked. Why couldn't it be simplified to just one mask at the first layers of encoder and d... |
H: Import image into Tensorflow model
I trained a simple Handwriting model with Tensorflow and MNIST:
(x_train, y_train), (x_test, y_test) = keras.datasets.mnist.load_data()
x_train = x_train.astype('float32')/255
x_test = x_test.astype('float32')/255
model = keras.Sequential([
keras.layers.Flatten(input_shape=(2... |
H: What’s the most suitable programming language for AI development?
For the past couple of years I’ve been learning how to use Python to script. But I would like to start getting into scripting more things like computers and AI. So, with that said, and please no hate, what in your opinion would be best to script th... |
H: Using the whole dataset for testing (not validation) in case of small datasets
for an object detection task I created a small dataset to train an object detector. The class frequency is more or less balanced, however I defined some additional attributes with environmental conditions for each image, which results in... |
H: What is the difference between TDNN and CNN?
I read about time delay neural network (TDNN) and I am not sure I understood it. From what I read it seems that tdnn works just like one dimensional convolutional neural network (CNN).
What are the differences between the architectures, if they exist?
AI: I found the an... |
H: Using Palmer Penguins Dataset Instead of Iris Flower Dataset
I have been trying to replace the Iris Flower dataset with the Palmer Penguin dataset for a neural network tutorial. I am using the tutorial at https://www.kaggle.com/antmarakis/another-neural-network-from-scratch
The Palmer Penguin dataset should be a go... |
H: Why fitting/training a model can be considered as learning?
I was looking around and I can't find a good answer, I just want to know why it can be considered as learning and is not just "calibration" or "parametrization".
I feel the word "learning" is overqualified for the things the models do.
Thanks in advance.
A... |
H: Which algorithm should I choose and why?
My friend was reading a textbook and had this question:
Suppose that you observe $(X_1,Y_1),...,(X_{100}Y_{100})$, which you assume to be i.i.d. copies of a random pair $(X,Y)$ taking values in $\mathbb{R}^2 \times \{1,2\}$. Your plot the data and see the following:
where bl... |
H: What does IBA mean in imblearn classification report?
imblearn is a python library for handling imbalanced data. A code for generating classification report is given below.
import numpy as np
from imblearn.metrics import classification_report_imbalanced
y_true = [0, 1, 2, 2, 2]
y_pred = [0, 0, 2, 2, 1]
target_name... |
H: Test set larger than train set
There is a two class dataset with 1121 values in total, having 230 from same class and 891 from the other class. The training set is choosen as 230+230=460 from both classes and the test set as the entire 1121 data.
1)Accuracy values are less than 0,50 even some are as low as 0,18 and... |
H: How to measure a almost (?) ordinal classification?
I have a model where I predict classes to define instructions for a trader robot. The classes are -2, -1, 1 and 2 (strong sell, light sell, light buy and strong buy) and I'm using a simple confusion matrix to asses the performance of the model, however I would lik... |
H: How to access GPT-3, BERT or alike?
I am interested in accessing NLP models mentioned in scientific papers, to replicate some results and experiment.
But I only see waiting lists https://openai.com/blog/openai-api/ and licenses granted in large commercial deals https://www.theverge.com/2020/9/22/21451283/microsoft-... |
H: How do the linear layers in the attention mechanism work?
I think I now the answer to my question but I dont really get confirmation.
When taking a look at the multi-head-attention block as presented in "Attention Is All You Need" we can see that there are three linear layers applied on the key, query and value mat... |
H: How to calculate the different metrics for multi class classification
My confusion matrix has the following structure:
(Predicted)
C= ( actual) [TN FP
FN TP]
How can I calculate the Mathews Correlation Coefficient (MCC) value for multi-class expressed as
MCC = (TP .* TN - FP ... |
H: Why removing rows with NA values from the majority class improves model performance
I have an imbalanced dataset like so:
df['y'].value_counts(normalize=True) * 100
No 92.769441
Yes 7.230559
Name: y, dtype: float64
The dataset consists of 13194 rows and 37 features.
I have tried numerous attempts to impro... |
H: How can I save my learning rate on each finished epoch using Callbacks?
I used LearningRateScheduler for my model training. I want to save learning rates on each epoch in CSV file (or other document files).
Is there any way to save those learning rates using callbacks?
AI: You may write a Custom Callback and save... |
H: ValueError: Input 0 of layer conv1_pad is incompatible with the layer: expected ndim=4, found ndim=3. Full shape received: [None, 224, 3]
I am trying to make a gender classifier. I am using MobileNet from Tensorflow with input shape as (224,224,3). After training the model, I tried to check if the model was working... |
H: what's the motivation behind BERT masking 2 words in a sentence?
bert and the more recent t5 ablation study, agree that
using a denoising objective always results in better downstream task performance compared to a language model
where denoising == masked-lm == cloze.
I understand why learning to represent a word... |
H: input shape of keras Sequential model
i am new to neural networks using keras,
i have the following train samples input shape (150528, 1235) and output shape is (154457, 1235) where 1235 is the training examples,
how to put the input shape, i tried below but gave me a
ValueError: Data cardinality is ambiguous:
x ... |
H: How to run unmodified Python program on GPU servers with scheduled GPUs?
Say I have one server with 10 GPUs. I have a python program which detects available GPU and use all of them.
I have a couple of users who will run python (Machine learning or data mining) programs and use GPU.
I initially thought to use Hadoop... |
H: Transformer architecture question
I am hand-coding a transformer (https://arxiv.org/pdf/1706.03762.pdf) based primarily on the instructions I found at this blog: http://jalammar.github.io/illustrated-transformer/.
The first attention block takes matrix input of the shape [words, input dimension] and multiplies by t... |
H: Accuracy goes straight for about 200 epochs then start increasing
Can anyone explain the following observation?
Why did the accuracies keep to be a straight line with a very smooth decrease of loss?
By the way, why is the loss lines so beautifully smooth for the first 400 epochs?
Is this because of the learning rat... |
H: How does tree-based algorithms handle linearly combined features?
While I am aware that tree-based algorithms (e.g., DT, RF, XGBoost) are 'immune' to multi-collinearity, how do they handle linearly combined features?
For example, is there is any additional value or harm in including the three feature: a, b and a+b ... |
H: How to train a model using a daunting huge training dataset
I have an extremely huge dataset and I'm wondering me how could be the right way to set an experiment to use this data to train a model.
I understand that I can use data-reduction to, for instance, drop out some variables. In despite data-reduction can act... |
H: whats wrong with the graph
I wanted to plot a bar graph which shows covid cases reported in different regions in different regions of USA.
So here is my code:
import pandas as pd
import matplotlib.pyplot as plt
datainput = pd.read_csv("MD_COVID-19.csv")
fig = plt.figure()
ax = fig.add_axes([0,0,1,1])
rgn1=list(data... |
H: How to calculate the "Evidence" for Naive Bayes text classification?
I'm trying to write a Naïve Bayes text classification from scratch in Python, but I can't quite grasp what I should do to write the actual classifier.
One question that popped up was: "What formula do you use?"
Do you use the Bayes Rule/Theorem? O... |
H: Is my model underfitting?
Model:
model = models.Sequential()
#add model layers
model.add(layers.Conv1D(64, kernel_size=3, activation='relu',padding='same'))
#model.add(layers.Conv1D(16, kernel_size=3, activation='sigmoid',padding='same'))
model.add(layers.MaxPooling1D( pool_size=2, strides=None, padding='same',... |
H: Does experience with Keras count as experience with Tensorflow?
Many Machine Learning job postings I've seen request experience with Tensorflow. If I have experience with Tensorflow, but only through building neural networks using the Keras API. Does that count?
I have yet to see a tutorial or any code anywhere tha... |
H: Which part should be frozen during transfer learning?
I want to use transfer learning and fine tuning and I need to decide which part of
the original model will be used and which part will be frozen. I'm thinking about four possilbe cases:
small/large new dataset and this set is similar/not similar to the original ... |
H: When would C become nescessary to do an analysis or manage data?
I use python in my day to day work as a research scientist and I am interested in learning C. When would a situation arise where python would prove insufficient to manipulate data?
AI: Most of the common libraries you would use for data manipulation ... |
H: Random Forest Classifier cannot recognise parameter grid
I am trying to run the below code to extract the feature importances of my random forest, but I'm getting the following error TypeError: init() got an unexpected keyword argument 'randomforestclassifier__max_depth'. Can anyone tell me what is wrong?
from skle... |
H: Changing the batch size during training
The choice of batch size is in some sense the measure of stochasticity :
On one hand, smaller batch sizes make the gradient descent more stochastic, the SGD can deviate significantly from the exact GD on the whole data, but allows for more exploration and performs in some se... |
H: Multi-Feature One-Hot-Encoder with varying amount of feature instances
Let's assume we have data instances like this:
[
[15, 20, ("banana","apple","cucumber"), ...],
[91, 12, ("orange","banana"), ...],
...
]
I am wondering how I can encode the third element of these datapoints. For multiple features va... |
H: Extract data from json format and paste to column using python
In my column with json data, I have this list I want to extract to column:
"list":[
{
"id":"list",
"item":[
{
"value":"Hergestellt in Italien aus 100% reinem Platin-Flüssigsilikon"
},
{
"value":"G... |
H: Once a predictive model is in production, how it can be evaluated?
I have a data science project, predicting customer's next purchase day. Customer's one year behavioral data was split to 9 and 3 months for train and test, using RFM analysis, I trained a model with different classifiers and the best one's result is... |
H: Is there any package in python that can identify similarity between alphanumeric alias names of a parameter?
For example: for a parameter like input voltage,
Alias names : V_INPUT, VIN etc.
Now, I want the software to recognize each of the alias names as same. Is there any package/method by which I can achiev... |
H: What does the oob decision function mean in random forest, how get class predictions from it, and calculating oob for unbalanced samples
I am interested in finding the OOB score for random forest using sklearn, when it is used for a binary classification task, and there are unbalanced samples. What does the oob dec... |
H: Find correlation between grades from two raters
The question is whether we can find a correlation between two sets of grades (categorical data).
Let’s say we have a dog competition and there are 1000 dogs participating.
There are two rounds of assessment
first round
dog owners give their assessment on the scale fro... |
H: Finding the duplicate values between all columns and sort in new column with Pandas?
I have this DataFrame:
CL1 CL2 CL3 CL4
0 a a b f
1 b y c d
2 c x d s
3 x s x a
4 s dx s s
5 a c d d
6 s dx f d
7 d dc g g
8 f x s t
9 c x a d
10 x ... |
H: Keras next(); what does (2, 256, 128, 128, 3) mean
I have used the next() method on a Keras generator. I then turned this into a numpy array to get the shape:
data = generator.next()
data = np.array(data)
print(data.shape)
>>> (2, 256, 128, 128, 3)
256 is my batch size, and (128, 128, 3) is my image size. But wha... |
H: Individual models gives quite same distribution on Test set, whereas Ensembling gives better result but very different distribution
I am working on a binary classification problem with unbalanced data (17% for positive class).
The problem is as following:
My three individual models when predicting on the test set (... |
H: How to properly set up neural network training for stable accuracy and loss
I have a DenseNet121 implemented in Pytorch for image classification. For now, the training set-up is pretty straightforward:
the data is loaded. An important characteristic here is that the validation data is fixed from the outset and can... |
H: "Rare words" on vocabulary
I am trying to create a sentiment analysis model and I have a question.
After I preprocessed my tweets and created my vocabulary I've noticed that I have words that appear less than 5 times in my dataset (Also there are many of them that appear 1 time). Many of them are real words and not... |
H: How to preprocess with NLP a big dataset for text classification
TL;DR
I've never done nlp before and I feel like I'm not doing it in the good way. I'd like to know if I'm really doing things in a bad way since the beginning or there's still hope to fix those problems mentioned later.
Some basic info
I'm trying to ... |
H: Does overfitting depend only on validation loss or both training and validation loss?
There are several scenarios that can occur while training and validating:
Both training loss and validation loss are decreasing, with the training loss lower than the validation loss.
Both training loss and validation loss are de... |
H: Unigram tokenizer: how does it work?
I have been trying to understand how the unigram tokenizer works since it is used in the sentencePiece tokenizer that I am planning on using, but I cannot wrap my head around it.
I tried to read the original paper, which contains so little details that it feels like it's been wr... |
H: Filenotfounderror: [errno 2] no such file or directory: 'nsr001.ecg'
I am trying to save contents of physiobank Normal Sinus Rhythm RR Interval Database into a numpy array but I keep getting an error:
Traceback (most recent call last):
File "AverageRRI.py", line 20, in <module>
averageArray = np.fromfile(file... |
H: How is the validation set processed in PyTorch?
Say, one uses the MNIST dataset and splits the provided training data of size 60,000 into a training set (50,000) and a validation set (10,000). The provided test data of size 10,000 is used as the test set. The ML algorithm is a neural network.
The training set is pr... |
H: Access keys of pandas dataframe when using groupby
I have the following database:
And I would like to know how many times a combination of BirthDate and Zipcode is repeated throughout the data table:
Now, my question is: How can I access the keys of this output? For instance, how can I get Birthdate=2000101 ZipCo... |
H: Deploying ML/Deep Learning on AWS Lambda for Long-Running Training, not just Inference
Serverless technology can be used to deploy ML models to production, since the deployment package sizes can be compressed if too large (or built from source with unneeded dependencies stripped).
But there is also the use case of ... |
H: Transformers understanding
i have i a big trouble. I don't understand transformers. I understand embedding, rnn's, GAN's, even Attention. But i don't understand transformers. Approximately 2 months ago i decided to avoid usage of transformers, because i found them hard. But i can't anymore avoid transformers. Pleas... |
H: Why is np.where not returning '1'? Only returns '0'
This code should return a new column called orc_4 with the value of 1 if the value of the row in df['indictment_charges'] contains 2907.04 or 0 if not.
Instead it is returning all 0's
for index, item in enumerate(df.indictment_charges):
s = '2907.04'
if s... |
H: Information leakage when train/test are truly i.i.d.?
I am well aware that to avoid information leakage, it is recommended to fit any transformation (e.g., standardization or imputation based on the median value) on the training dataset and applying it to the test datasets. However. I am not clear what is the risk ... |
H: Importance of normal Distribution
I have been reading about probability distributions lately and saw that the Normal Distribution is of great importance. A couple of the articles stated that it is advised for the data to follow normal distribution. Why is that so? What upper hand do I have if my data follows normal... |
H: Python stemmer for Georgian
I am currently working with Georgian texts processing. Does anybody know any stemmers/lemmatizers (or other NLP tools) for Georgian that I could use with Python.
Thanks in advance!
AI: I don't know any Georgian stemmer or lemmatizer. I think, however, that you have another option: to use... |
H: Math of Logistic regression cost function
In the current scikit-learn documentation for binary Logistic regression there is the minimization of the following cost function:
$$\min_{w, c} \frac{1}{2}w^T w + C \sum_{i=1}^n \log(\exp(- y_i (X_i^T w + c)) + 1)$$
Questions:
what is the $c$ term? It is not explained in ... |
H: Dimensionality reduction convolutional autoencoders
I don't understand how convolutional autoencoders achieve dimensionality reduction. For FFNN based autoencoder, the reduction is easy to understand: the input layer has N neurons, and the hidden ones have M neurons, where N is greater than M.
Instead, in a convolu... |
H: Semantic segmentation of an image with multiple labels per pixel
I am building a model for a multiclass sematic segmentation of a skin disease. At a moment I am using U-Net for binary classifications.
In this multiclass problem I have the following cases. There are four types of skin damage. There are four degrees ... |
H: Backpropagation of a transformer
when a transformer model is trained there is linear layer in the end of decoder which i understand is a fully connected neural network. During training of a transformer model when a loss is obtained it will backpropagate to adjust the weights.
My question is how deep the backpropaga... |
H: What are the inputs to the first decoder layer in a Transformer model during the training phase?
I am trying to wrap my head around how the Transformer architecture works. I think I have a decent top-level understanding of the encoder part, sort of how the Key, Query, and Value tensors work in the MultiHead attenti... |
H: Feature and the Gaussian Distribution (classification)
I have a question regarding variable following or not a random distribution.
I selected 4 features negatively correlated to the label (Fraud/No Fraud). The notebook I'm taking the inspiration from plotted the distribution of these feature regarding the label. W... |
H: Are all 110 million parameter in bert are trainable
I am trying to understand are all these 110 million parameters trainable of bert uncased model. Is there any non trainable parameters in this image below?
By trainable I understand they are initialized with random weight and during pretraining these weights are ba... |
H: Why does storing the output of .count() result in all 1's or 0's?
I have a dataframe which I run loc on to find all values within the loc parameters. Whatever the loc returns gets stored in a variable. I try to use this variable to store it in another dataframe column but it only returns 1's and 0's for the whole c... |
H: How to show two pictures in one cell in Jupyter Notebook? (matplotlib) (python)
As a beginner, can someone please help me with this? Is there any way to show both pictures in a single cell's output? My output could only display one picture. Thank you for your time and attention!
Here is my code:
from skimage impo... |
H: The upper range of a collected dataset is most likely accurate, but the rest may suffer biased omissions: How to call this phenomenon?
Background: In collecting a dataset of a specific unit ordered by a numeric variable, it is possible that the upper 'cloud' of the dataset is correct, while the 'tail' seems inaccur... |
H: Hyperparameter tuning with Bayesian-Optimization
I'm using LightGBM for the regression problem and here is my code.
def bayesion_opt_lgbm(X, y, init_iter = 5, n_iter = 10, random_seed = 32, seed= 100, num_iterations = 50,
dtrain = lgb.Dataset(data = X_train, label = y_train)):
d... |
H: Would there be any reason to pretrain BERT on specific texts?
So the official BERT English model is trained on Wikipedia and BookCurpos (source).
Now, for example, let's say I want to use BERT for Movies tag recommendation. Is there any reason for me to pretrain a new BERT model from scratch on movie-related datase... |
H: Find parameters to maximise output score
Not sure this is the right place to ask. Lets say there is a function f() where its implementation is unknown but it returns a score. I would like to get the highest possible score by modifying the input parameters. I also try to be better than brute force (finding all possi... |
H: Features selection in imbalanced dataset
I have some doubts regarding an analysis. I have a dataset with class imbalance. I am trying to investigate some information from that data, e.g., how many urls contain http or https protocols.
My results are as follows:
http in dataset with class 1: 10
http in dataset with ... |
H: Understanding the last two Linear Transformations in LeNet-5
I need help with understanding the LeNet-5 CNN:
How/Why does FC3 and FC4 have 120 and 84 parameters?
How are the filters 6 and 16 chosen? (intuition based on the dataset?)
Everywhere that I have looked, I haven't found an answer to #1, including LeCunn... |
H: What are the activation functions in Convolutional Layers for?
I read a lot about CNNs but I didn't quite understand some things:
What are the activation function in CLayers for? If I understood it right, the only weights in these layers are the ones in Filters, and for the activation function a weighted sum is ne... |
H: Chi-Squared test: ok for selecting significant features?
I would have a question on the contingency table and its results.
I was performing this analysis on names starting with symbols as a possible feature, getting the following values:
Label 0.0 1.0
with_symb 1584 241
without_symb 16 14
g... |
H: Correlations, p-values and features selection
By using correlation matrix, I got some results:
Count_words -0.098857
Count_numbers -0.008305
Count_symbols -0.025853
Count_question -0.031649
Count_equal 0.224223
Count_characters 0.09
I used this line of code (in case you ... |
H: Selecting most important features for multilinear regression
I have a set of 25 features. I would like to choose the best features for my model. Originally, I was looking at the correlation of features with respect to response, and only taking those which are highly correlated and run a regression model. Then, usin... |
H: Keras weird loss and metrics during train
I am doing some testing with tensorflow, and I bumbed into a very weird behaviour.
Here is my code
fashion_mnist = tf.keras.datasets.fashion_mnist
(train_images1, train_labels), (test_images, test_labels) = fashion_mnist.load_data()
train_images = train_images1[:32] / 255.0... |
H: How can i solve the classification's problem with cross validation in LogisticRegression?
I want to make a data frame with most repeated word in sentences and make a classification via Logistic-Regression.
I tried to write the steps clearly in codes.
The column B is my target.
What I have: (Sample)
raw_data={"... |
H: Using R to organize/rearrange CSV - group by multiple columns?
I have a CSV that I need to clean up / organize in a usable way using R. I need to group by the property ID and then want to take all the unique years for the defor year column and make each year into a sperate column with the amount of deforestation fo... |
H: Pytorch's CrossEntropyLoss?
Can anybody explain what's going on here? I thought I knew how cross entropy loss works.
I have tried with Negativeloglikelihood as well?
AI: The problem is that, in Pytorch, CrossEntropyLoss is more than its name suggests. The documentation says that:
This criterion combines nn.LogSof... |
H: Getting very low/ wrong accuracy from RandomizedSearchCV
I am currently using RandomizedSearchCV to optimize my hyper-parameters. However the reported scores of each iteration is very low. When I then evaluate the highest scoring candidate I get very high accuracy (0.97), while the RandomizedSearchCV reports someth... |
H: Can Micro-Average Roc Auc Score be larger than Class Roc Auc Scores
I'm working with an imbalanced data set. There are 11567 negative and 3737 positive samples in train data. There are 2892 negative and 935 positive samples in validation data. It is a binary classification problem and I used Micro and Macro average... |
H: Undersampling for credit card fraud detection before or after Train/Test Split
I have a credit card dataset with 98% transactions are Non-Fraud and 2% are fraud.
I have been trying to undersample the majotrity class before train and test split and get very good recall and precision on the test set.
When I do the un... |
H: Creating parallel keras layers
I am new to Keras and ML and I want to create a NN that can seperate a bitmap-like image into its visual components.
My approach is to feed a two dimensional image (lets say 8 by 8 pixels) into a NN, which then outputs a three dimensional matrix (e.g 3 by 8 by 8). Every element of the... |
H: Sum of squares for matrix valued data over $\mathbb{R}$ and $\mathbb{C}$
Let us assume we have $k \times k$ matrix valued data and assume this is organized (possibly as time series):
$$ M_1, M_2, \ldots, M_n $$
Now, assume we are interested in writing down an error function that mimics sums of squares. This can nai... |
H: Dealing with dates in dataframe
I have a dataframe which has two date columns - Start Date and End Date,
Let's suppose start date is 4/10/2019 and end date is 4/10/2020 (MM/DD/YYYY) now I want to split these dates in a list which will have all the intermediate months (from october 2019 to october 2020). Is there an... |
H: How to Iterate over rows in a dataframe
So I've been trying to iterate over rows of my dataframe and my goal is to find matching rows based on two particular columns (say C and P). Then i need to do some manipulations as well in the data for the rows. I've read quite a few answers here telling to use iterrows() or ... |
H: Issue translating large amounts of tweets using Google Translate
I am working on translating large amounts of tweets using this deep-translator which uses the Google Translate API.
Initially everything was fine and tweets were translated with no problems whatsoever but I recently encountered an issue.
The issue wit... |
H: MLP sequential fitting
I am fitting a Keras model, using SGD
Input dataset X_train has 55000 entries.
Can anyone explain the yellow highlighted values?
For me, when each epoch is done, this should correspond to 55000/55000.
model = keras.models.Sequential()
model.add(keras.layers.Flatten(input_shape=[28,28]))
mode... |
H: Regression analysis and least square method relation?
I want to know where Regression analysis is most used at, what's its competitor methods, and how least square method relates to regression analysis.
AI: I want to know where Regression analysis is most used at
Regression analysis is used for analyzing the relat... |
H: Does the model(best fitting line/curve) changes when the training data is changed in the cross validation?
From my understanding - a machine learning algorithm goes through the inputs (independent variables) and predicts the output (dependent variable). I believe, what line/curve would best define the training data... |
H: Tensorflow's .shuffle(BUFFER_SIZE)
I came across the following function in Tensorflow's tutorial on Machine Translation:
BUFFER_SIZE = 32000
BATCH_SIZE = 64
data_size = 30000
train_dataset = train_dataset.shuffle(BUFFER_SIZE).batch(BATCH_SIZE, drop_remainder=True)
I went through several blogs to understand .shuffl... |
H: p-value and effect size
Is it correct to say that the lower the p-value is the higher is the difference between the two means of the two groups in the t-test?
For example, if I apply the t-test between two groups of measurements A and B and then to two groups of measurements B and C and I find that in the first cas... |
H: Sort Pandas Dataframe per column
I have a dataset with age + another 14 variables. I have created 13 bins representing different age groups like so:
data["age_bins"] = pd.cut(data["age"], [16,20,25,30,35,40,45,50,55,60,65,70,75,80])
Then calculated the mean value of those 14 other variables per age group like so
d... |
H: What is the num_initial_points argument for Bayesian Optimization with Keras Tuner?
I've implemented the following code to run Keras-Tuner with Bayesian Optimization:
def model_builder(hp):
NormLayer = Normalization()
NormLayer.adapt(X_train)
model = Sequential()
model.add(Input(shape=X_t... |
H: Where to get models with weights instead of only weights? What's the purpose of .h5 files?
I have downloaded .h5 files from qubvel/resnet and qubvel/efficientnet. I was trying to use some models as a backbone for my model but I'm getting the following error:
ValueError: No model found in the config file.
As explai... |
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