Keras unsupervised classification jobber

The aim is to build an AI classifier which will accurately predict whether a given URL link is malicious or not based on the datasets that the classifier has used for training and testing the data. I will provide the webpage classification train and test data so that the classifier can be built. The aim is get any URL and the relevant parameters (extracted using an API) and pass it to this AI classifier hosted on the cloud - which will determine whether it is malicious or not based on the same parameters used within the provided datasets.

proofreading and modification if needed for a PhD proposal in computer science (image classification)

I would like an expert in R software (or RStudio) regarding machine learning methods, specifically boosted regression tree, random forest, and classification and regression tree for land subsidence susceptibility mapping. He/she will have to input the data that we have already processed to the R software to produce a susceptibility map.

A binary classification between MCI and CN classes with considerable performance and compare between both 3d & 2d cnn with dataset and output visualization ... adni data set with maximum number of volumes as possible. Video recording for the whole process. Comments in code

I need you to build an email spam classification using Naive-Bayes, SVM, and Logistic Regression models. Also, I need statistical tests to be performed on the model. Like t-tests, z-tests, hypotheses tests, CI tests etc. Let me know if you can work on this. I need this urgently.

Applying machine learning algorithms on fake news dataset in R language

I would like an expert in R software (or RStudio) regarding machine learning methods, specifically boosted regression tree, random forest, and classification and regression tree for land subsidence susceptibility mapping. He/she will have to input the data that we have already processed to the R software to produce a susceptibility map.

We are looking to build an 8 Page Event Promoter Website with clean and fresh graphics and use friendly with high appeal, SEO, easy to edit and upload images. The website will have 2 sections, KENYA and AUSTRALIA. So people can visit which country they want to view. The website is primarily used to display our work, past, current an...photo albums and promotional video content that we upload 7. Newletter and mailchimp intergration Do not send me generic applications. I require you to actually read the content and work required before reading your application. Customise your application with what we actually require. We need a website designer who can think outside the box and is creative with fresh ideas and can work unsupervised. A sample design will be required before we ...

should perform naive bayes classification method on data and should write report

Hi there! I’m looking for a Data Scientist/Machine Learning Engineer with python proficiency. We need to build and test a general hyper parameter optimization method for TF models classification/regression models. The method need to run several training attempts (but not all the possible combinations) over a universe of hyper parameters like: • Number of layers of the NN • Learning rate • Number of dropout layers • Activation functions • Neurons per layer • Others We expect a method that can optimize the runs in order to decrease the number of trainings. For this project the following tasks are required: 1. Design the method (input, output parameters). 2. Implement the method using python and tensorlfow. 3. Test the method over two well-known dat...

Hi there, As agreed, your task is to extract all of the links from the website I sent you and supply me the fields in a spreadsheet (Microsoft Excel current version format): The fields to be supplied are: Name (the plain english name of the item) Category (the category classification the site has assigned to the item) Main URL (the URL of the main page for the item, which is hosted on the above site) Final URL1 (the URL of the first download page for the item, which is hosted on a different site) Final URL2 (the URL of the second download page for the item, which is hosted on a different site) Final URL3 (the URL of the third download page for the item, which is hosted on a different site) Final URL4 etc (the URL of the fourth or more download pages for the item, which are hosted...

Vehicle classification for traffic videos in python

I want to understand what is the unique value of Lithuania and its laser technology makes it take more than 50% of the laser market. Questions to be answered: 1. What is the laser technology and its sub technologies? Mapping from technologies to applications. 2. What is the unique laser technology in Lithuania? What is it's position in Europe? What classification is its belonged to in the overall laser technology (tech map from question 1) 3. What are the top 3 companies from Lithuania in laser industry? What they key products and achievement? 4. Who are the top 10 researchers from Lithuania in laser industry? What are the key achievement, contribution, academic position(in terms of quality and quantities) Report in PPT format with comments No limit for number of slides as l...

We are working in the healthcare sector generating synthetic medical images. We are working with Generative Adversarial Networks, Markov Chain Generators and maybe Bayesian Networks. We would require support in developing the models. Languages: R, Keras/ Tensorflow

A review article about Nanocomposites technology for CO2 separation will be written from the analysys of 50 papers. The conformation of the article will be done following the methodology below: - Gather all related papers (50) - Make grouping of them ( groups of the similar papers in methods, techniques, etc. Means classification of papers. - Criticize each group. Means talking about what each paper and group did. Efficient comparison. In simple words and tables. - Conclusions The work will be done within 20 days from 12/04/2022 with advances and progress reports every 5 days, that means: 1st progress: April 17 2nd: April 24 Final: 1 may.

Time Sensitive: 4/14 11:59 PST Code a DCGAN and/or proGAN model that can take a random noise image or feature template image and generate images of dark skin conditions (Melanoma) using Keras (preferably in Google Colab too) Pricing: $150 (negotiable) Attached is the Melanoma Images (some graphic) & my current Pix2Pix GAN If you have any questions, please contact me!

Hi , I need Python developer with ML experience (1-4Yrs), Python with OCR - Tensor flow , Keras-OCR Java Script knowledge or any JS frame would be added advantage . Whole project details should be shared in one to one discussion.

Looking forward to expert in R programming well-versed in Unsupervised Learning Approaches such as Time Series, Clustering (Basic and Advanced), Association Rules, Neural Networks, Recommendation systems. You must be an expert in the conceptual and coding aspects of R and possess a good grasp of these machine learning approaches.

You can use any image retrieval using deep learning. from github etc It should work and the results should be reproducible. The project is about mAP (mean average precision). Your code should calculate mAP for arbitrary number of query images. Keras and TF.

...experiments to be conducted would vary. 2 Problem statements We consider five distinct tasks for the assignments which are described below: 2.1 Binary Classification problem Here we consider a 2 class classification problem on image data. The dataset is PneumoniaMNIST which can be found here: It contains images from chest X-rays belonging to two classes - Normal and Pneumonia. The metrics to be computed are: classification accuracy, AUC and F1 score. Training is to be done on the training split and test on the test split. 2.2 Multi-Class Classification Problem In this task, we look at an 8-class classification problem on Blood Cell Microscope images. The dataset is called the BloodMNIST which can be obtained from this link -

I need help in a simple Web-based application that can analyze Arabic reviews by sentiment analysis and text classification for a graduation project.

...experiments to be conducted would vary. 2 Problem statements We consider five distinct tasks for the assignments which are described below: 2.1 Binary Classification problem Here we consider a 2 class classification problem on image data. The dataset is PneumoniaMNIST which can be found here: It contains images from chest X-rays belonging to two classes - Normal and Pneumonia. The metrics to be computed are: classification accuracy, AUC and F1 score. Training is to be done on the training split and test on the test split. 2.2 Multi-Class Classification Problem In this task, we look at an 8-class classification problem on Blood Cell Microscope images. The dataset is called the BloodMNIST which can be obtained from this link -

I have a data set of 209 X 20000 dimensions. And each of the 209 rows predicts a target class. I want a pipeline to successfully classify these target class labels. Classification, supervised algorithms are required.

It is a 75% complete project. Need some new additions in it. Need to create a data set using MATLAB and POFACETS there after need to integrate this data set into the existing project. Bidders from Hyderabad, India preferred. I shall share the project details and requirements.

...by a pair (X, C), where X is a set of Boolean variables and C is a set of clauses in Conjunctive Normal Form (CNF). Each clause is a disjunction of literals (a variable or its negation). This problem is well known as the classic NP-complete problem. Recent advances in supervised learning have provided powerful techniques for classifying problems. In this project, we see the SAT problem as a classification problem. Given a Boolean formula (represented by a vector of features), we are asked to predict if it is satisfiable or not. In this project, we represent SAT problems with a vector of 327 features with general information about the problem, e.g., number of variables, number of clauses, fraction of horn clauses in the problem, etc. The CSV dataset file attached contains 1929 row...

A classification model is to be developed using Decision Trees Based Methods

I have few images and want to classify them by Train images using supervised and unsupervised ai based ml methods

I need to build a very basic python program for prediction. To predict we need to test and train the dataset by apply machine learning algorithms for classification and regression and power BI/tableau to show case the various combination of these predication on Dashboard/charts/graphs.

I would like an expert in R software (or RStudio) regarding machine learning methods, specifically boosted regression tree, random forest, and classification and regression tree for land subsidence susceptibility mapping. He/she will have to input the data that we have already processed to the R software to produce a susceptibility map.

...equation should be optimised. It should be optimised to maximise the performance of the binary classification. 2) From the single optimal equation that combines the out from sensor A and sensor B. What is the optimal threshold or cutoff to give the best classification. Further considerations: - Must be completed with Matlab. This can include any of the toolbox functions. - Code should be fully commented and easy to understand. - A short report should be provided. This will include: i) background/basics of the approach used, ii) explanation and figures to illustrate how the approach works, iii) figures and text to show that the approach is optimal, iv) figures and text to demonstrate the classification performance. - Last point. It is possible that the approach ...

Need to do coding in python by implementing deep few-shot learning hyperspectral image classification in precision agriculture. Dataset already got. The objective is :- design hyperspectral transformation to maximize relevance to precision agriculture using deep few-shot learning. 2. To implement deep few-shot learning (DFSL) for hyperspectral image classification in precision agriculture using a small training dataset. 3. To evaluate hyperspectral transformation to increase the amount of hyperspectral picture data relevant to precision agriculture using precision, recall, and F1 score.

I want to implement my deep learning image classification model in to the tansorflow lite in android studio.

Mild cognitive impairment (MCI) is one of the types of memory loss in w...memory. If the patient with MCI is not identified in the early stages, this may lead to Alzheimer’s disease (AD). In this paper, a hybrid algorithm is developed to diagnose the MCI in the early stages. The Renyi Entropy (RE) and Discrete Wavelet Transformation (DWT) is used to extract the features from Electroencephalography (EEG) signals. Then these extracted features are given as input to the classification algorithms like Support Vector Machine (SVM), Decision Trees (DT), K-Nearest Neighbor (KNN) and to hybrid algorithm ACO+KNN (combined ACO with K-NN). The comparison between 4 machine learning algorithms with two feature extraction techniques is shown in this paper. The performance is calculated base...

The task is about to use image proceszing, neural network, AI , classification in order to train and build the model according to requested task Regured tehnolog: Phyton

I had a small code that I wrote for the program I don't know if you want to use it or not. its a very small code not a big one. small(X) :- X < 50. medium(X) :- X >= 50, X =< 100. big(X) :- X > 100. % classify(+N, ?Classification) classify(N, small) :- ...guard...test N for smallness... classify(N, medium) :- ...guard...test N for mediumness... classify(N, big) :- ...guard...test N for bigness... classify(N, small) :- must_be(number,N), N < 50, !. classify(N, medium) :- must_be(number,N), N >= 50, N =< 100, !. classify(N, big) :- must_be(number,N), N > 100.

Car Seat belt detection using python, tensorflow and keras max one day

TF-IDF, Principal Component Analysis (PCA) and non-Negative Matrix Factorization (NMF), Logistic/Linear Classification and Support Vector Machines, Grid-Search and Cross Validation

Attached notebook should be carefully converted to Keras from Pytorch. The results must be exactly similar. Budget is $20. 2-3 days If you are going to bid more than $30, do not bother yourself to bid or try to convince me in the chat. It is super simple project if you know pytorch and keras.

Two hidden layers here means (input - hidden1 - hidden2 - output). You must not use flax, optax, or any other library for this task. Use MNIST dataset with 80:20 train:test split. Manually optimize the number of neurons in hidden layers. Use gradient descent from scratch to optimize your network. You should use the Pytree concept of JAX to...output). You must not use flax, optax, or any other library for this task. Use MNIST dataset with 80:20 train:test split. Manually optimize the number of neurons in hidden layers. Use gradient descent from scratch to optimize your network. You should use the Pytree concept of JAX to do this elegantly. Plot loss v/s iterations curve with matplotlib. Evaluate the model on test data with various classification metrics and briefly discuss their impl...

Need by tomorrow: help with binary classification in Python

Hi Maksym M., I noticed your profile and would like to offer you my project. We can discuss any details over chat.

Hi Hemdan K., I noticed your profile and would like to offer you my project. We can discuss any details over chat.

Hi Nashi R., I noticed your profile and would like to offer you my project. We can discuss any details over chat.

Hi Dat D., I noticed your profile and would like to offer you my project. We can discuss any details over chat.

Hi Mahmoud E., I noticed your profile and would like to offer you my project. We can discuss any details over chat.

Hi Vladimir B., I noticed your profile and would like to offer you my project. We can discuss any details over chat.

...numbers and document classification dropdown that supportive of our branding colours and logo. A little bit more than just our logo in the top right hand corner, but not too much it's overbearing. All with formatting for headers and list bullets, contents table with appropriate font and colour so its ready to use. I do not want the default blue word headers you get with word for example, but it must look professional. (tab space 1cm etc) 3. Branded Letter template for formal communications with all our details, letter formation and prompts for filling in variable text. 4. Word Document that can be used for Policy Documents / Strategy documents etc that requires a Cover Page with things like document references such as: title, author, approver, date of creation, class...

We are doing a small project on image orientation estimation using cnn. The task is to build and evaluate the cnn model for our project we are using celebA dataset that is available in keras.

Regression and classification problems

I have a neural network model for a binary classification problem, I need a confusion matrix to evaluate the performance and calculate different metrics like accuracy, recall etc