skunk | A data access library for Scala + Postgres | Functional Programming library

I have a problem about implementing recommendation system by using Euclidean Distance.

What I want to do is to list some close games with respect to search criteria by game title and genre.

Here is my project link : Link

After calling function, it throws an error shown below. How can I fix it?

Here is the error

When i use sudo apt update command in terminal to see if there are a new updates for packages i get repository error like below :

I have a simple, multiple question quiz that displays certain text when the correct or incorrect answer is selected. Now I am trying to add an incremental score, but am having no success. I have added an alert, which fires whether the answer is correct or incorrect, but the score does not increment.

What am I missing in my code?

The full code is included below. Only one question has been included to keep it simple.

I have a query regarding the extraction of VGG16/VGG19 features for my experiments.

The pre-trained VGG16 and VGG19 models have been trained on ImageNet dataset having 1000 classes (say c1,c2, ... c1000) and normally we extract the features from first and second fully connected layers designated ('FC1' and 'FC2'); these 4096 dimensional feature vectors are then used for computer vision tasks.

My question is that can we use these networks to extract features of an image that does not belong to any of the above 1000 classes ? In other words, can we use these networks to extract features of an image with label c1001 ? Remember that c1001 does not belong to the Imagenet classes on which these networks were initially trained on.

In the article available on https://www.pyimagesearch.com/2019/05/20/transfer-learning-with-keras-and-deep-learning/, I am quoting the following -

When performing feature extraction, we treat the pre-trained network as an arbitrary feature extractor, allowing the input image to propagate forward, stopping at pre-specified layer, and taking the outputs of that layer as our features

From the above text, there is no restriction to whether the image must necessarily belong to one of the Imagenet classes.

Kindly spare some time to uncover this mystery.

In the research papers, the authors simply state that they have used features extracted from VGG16/VGG19 network pre-trained on Imagenet dataset without giving any further details.

I am giving a case study for reference:

Animal with Attribute dataset (see https://cvml.ist.ac.at/AwA2/) is a very popular dataset with 50 animal classes for image recognition task. The authors have extracted ILSVRC-pretrained ResNet101 features for the above dataset images. This ResNet 101 network has been pre-trained on 1000 imagenet classes (different imagenet classes are available at https://gist.github.com/yrevar/942d3a0ac09ec9e5eb3a#file-imagenet1000_clsidx_to_labels-txt).

Also, the AWA classes are put as follows:

I have two different dataframes: A, B. The column Event has similar data that I'm using to compare the two dataframes. I want to give Dataframe A a new column, dfA.newContext#.

In order to do this, I'll need to use the Event column. I want to iterate through Dataframe A to find a match for Event and assign the dfB.context# to dfA.newContext#

I think a loop would be the best way since I have a few conditions that I need to check.

This might be asking a bit much but I'm really stuck.. I want to do something like this:

I would like to generate a random word from an array and then change the innerHTMl of an element to that word. However I would like this to happen so that multiple client browsers are receiving the same word. Currently every browser is receiving a random word however not the same random word. I understand why this is happening - the function is being called in every browser and therefore generating a unique random word to that browser. How do I ensure that the same randomly generated word is sent out to each individual browser?

Code below:

Index.Js (server side)

When adding an ngFor to a div I get the following warning and it appears to be stopping my HTML from rendering.

I only have the one module on my app and the BrowserModule is imported in the imports which seemed to fix the problem for most people but it's not working for me.

HTML:

getting this error when using the Cifar-100 dataset. I'm pretty sure I have the correct input shape and I have an output layer of 97, which are all the possible outputs in the dataset. What might I be doing wrong? Note: I am new to ML and Tensorflow, teach me some things please. :)