Naive bayes classifier jobber

Implement a BERT model for text classification to filter emotions of Twitter posts based on their content.

I'm seeking a data mining expert to rework my project's problem statement, craft novel project objectives, and link the methodology with a literature review. I'm primarily focusing on Stacking classifier and Hybrid stacking models. The ideal candidate should have a strong background in these models to help develop a completely new approach for my project. Key requirements for this role include: - Expertise in classification models, especially Stacking classifier and Hybrid stacking - Strong experience in data mining and methodology development - Proven track record of combining insights from multiple studies - Ability to write a comprehensive literature review and identify gaps in existing studies Your role will be crucial in not only improving the problem ...

i want to make chatbot, now i'm using naive bayes but accuracy score is 0. i don't know how to fix it. i have dataset question and answer arround 190 row. need cheap price.

...that is accessible and engaging for beginners - The ability to track user progress and provide feedback If you have a passion for teaching and a strong background in machine learning, I would love to hear from you. Please provide examples of similar work you have done in the past. #Machine Learning Algorithms# -Linear regression -Logistic regression -Decision tree -SVM algorithm -Naive Bayes algorithm -KNN algorithm -K-means -Random forest algorithm -Dimensionality reduction algorithms -Gradient boosting algorithm and AdaBoosting algorithm #Types of Machine Learning Algorithms# -Supervised Learning -Unsupervised Learning -Semi-supervised Learning -Reinforcement Learning I need totally 14 article. Each article must consist of 1500 words. Pyt...

...User-friendly design that is accessible and engaging for beginners - The ability to track user progress and provide feedback If you have a passion for teaching and a strong background in machine learning, I would love to hear from you. Please provide examples of similar work you have done in the past. #Machine Learning Algorithms# -Linear regression -Logistic regression -Decision tree -SVM algorithm -Naive Bayes algorithm -KNN algorithm -K-means -Random forest algorithm -Dimensionality reduction algorithms -Gradient boosting algorithm and AdaBoosting algorithm #Types of Machine Learning Algorithms# -Supervised Learning -Unsupervised Learning -Semi-supervised Learning -Reinforcement Learning I need totally 14 article. Each article must consist of 1500 words. Python s...

...Experience in feature engineering, data preprocessing, and model selection - Excellent problem-solving abilities these are the machine learning algorithms. We can use some of the following whichever is easy to write the thesis Sir 1. Logistic Regression 2. Support Vector Machines (SVM) 3. Decision Trees 4. Random Forest 5. Gradient Boosting Machines (GBM) 6. K-Nearest Neighbors (KNN) 7. Naive Bayes 1. Linear Regression 2. Polynomial Regression 3. Ridge Regression 4. Lasso Regression 5. Elastic Net Regression 6. Support Vector Regression (SVR) 7. Decision Tree Regression 1. K-Means Clustering 2. Hierarchical Clustering 3. DBSCAN (Density-Based Spatial Clustering of Applications with Noise) 4. Mean Shift Clustering 5. Gaussian Mixture Models (GMM) 6. Agglomerative Cl...

...field of Natural Language Processing to develop a Multimodel Classifier of memes which takes text and image as input(seperate datasets are present for both text and image') and classify the meme into given labels for my project. here is my project Key Tasks: - Handling various Natural Language Processing tasks such as text classification, image classification - Development of a Multimodel Classifier that can effectively analyze text and images. Requirements: - Proficiency in Python for implementing the Multimodel Classifier. - Prior experience in Natural Language Processing and developing classification models. - Ability to work with text and image data for training the classifier. It's essential that the freelancer has a strong understandin...

I want diabetes prediction using all types of algorithm -svm, knn, linear regression logistic regression, naive bias, random forest, regression analysis, ensemble learning. All of the model should show the accuracy rate of prediction. A graphical pie chart showing which model is giving how much accuracy and validation loss. So that we can say that ml algorithm is best for diabetes prediction. I want a tableau visualization showing all of these predictions correctly A webapp using flask and a jotform for user to use and predict easily. If you can successfully deliver I would like to work on a thesis paper for publication

...ideally, has previous experience with Graph Neural Networks (GNN). The goal is to create a classifier that can distinguish between two classes - 0 and 1 - based on edge weights. Key Task Components: 1. Use of Python programming language for GNN classifier implementation. 2. Incorporate UNSW-NB15 Dataset to structure the graph with nodes and edges. 3. The classifier should focus specifically on the features of edges for classification. 4. Deliverable will be a GNN implementation that will classify edges of the graph using edge features This project requires knowledge of Python, GNN, and familiarity with the UNSW-NB15 Dataset. Your ability to conceptualize, develop and deliver a working GNN classifier, focusing on edge weights, is essential. Previous exp...

I'm seeking the expertise of a data scientist or machine learning engineer to develop a model for classifying various types of attacks on a KDD dataset. The ideal candidate will have extensive knowledge in the use of autoencoders for feature extraction and GRU models. Key project elements include: * Professionals will need to implement an autoencoder for feature extraction with the core goal of reducing data dimensionality. Prior experience in working with high-dimensional data and in deploying autoencoders is necessary. * Subsequently, the system built should be capable of classifying Denial of Service (DoS), User to Root (U2R), and Probe attacks within the KDD dataset. Good working knowledge of GRU models and the mentioned attacks is required. * The project includes steps to ensure...

I am seeking an experienced ML Engineer to develop a sophisticated image classification model for landscapes, particularly focusing on roads, tracks, and trails. It will need to accept Geojson files or Cadastre files. Requirements: - Build and train an ML model to identify and classify roads, tracks, and trails in landscape images. - Integrate the model with current software to replace or enhance existing classification features. Further Breif: 3 weeks deadline Skills and Experience: - Previous work with image classification models. - Experience in machine learning and artificial intelligence. - Ability to work with intricate image data related to landscapes. - Strong understanding of algorithms used in identifying and classifying object types. Framework The model is to be host...

I'm seeking a deep learning specialist to execute an assignment focused on using a Generative Adversar...improvement. You need to report Frechet Inception Distance (FID) and Inception Score (IS). Experiments to perform: 1. Train cGAN and generate images according to the class labels. 2. Evaluate the generated images (at least 10 for each class) by considering them as test images and report the accuracy. Compare the accuracy with original test set images of the dataset. For this, you can train any classifier of your choice with the training data available to you. The dataset includes: • train data: training images. • train labels: training labels. • train sketch: unpaired training sketches. • test data: test images. • test labels: test labels. • tes...

I have approximately 10,000 images that need to be classified into 5 categories: ethnicity, hair type, physical attributes, body type, and a general category called misc. I need a model that is flexible, can handle images that may fit into multiple categories, and is reusable for future images as our database grows. Key areas that will require attention are: - The 'misc' category: The model should consider clothing aspects of the image. - Hair type classification: The model should be attuned to the color of the hair. - Body type classification: the model should consider athletic, curvy and petite as a baseline. I am interested in finding someone with strong experience in image categorization in nuanced settings using machine learning techniques. Experience working with content ...

Title: Seeking Freelance Developer for Mobile-Responsive News Classifier Website Introduction: We are seeking a skilled freelance developer to collaborate on an exciting project to build a mobile-responsive website that classifies news articles into "Good News" and "Bad News" categories. This project aims to provide users with a user-friendly platform to access and analyze news content based on sentiment analysis. Project Overview: The primary objective of this project is to develop a mobile-responsive website with the following features: News Aggregation: Collect news articles from specific sources, which are addable and configurable. Sentiment Analysis "AI": Analyze the sentiment of each news article to classify it as either "Good News" o...

Vennligst Registrer deg eller Logg inn for å se detaljer.

I want a proficient developer to create a recommendation system geared towards library users. It should employ a variety of machine learning techniques including KNN, MF, Association Rule Mining, Decision Tree, Naive Bayes, MLP, and Ensemble Learning. The system’s effectiveness should be evaluated using several methods as below: - RMSE - MAE - MSE - Accuracy - Precision Recall - F1 score Use Book Crossing Dataset Code must be in python and don't use specific recommender system library i.e., surprise etc. The successful freelancer must have appreciable knowledge and expertise across these various machine learning techniques, and previous experience building effective recommendation systems. Experience working on recommendation systems for a library or similar ins...

I'm seeking a proficient developer to build a cutting-edge fire and intruder detection system utilizing the yolov5. Crucial to this project is the use of an IP camera, which will be the primary source for the footage to analyze. Key Features: - Implement yolov5 technology to effectively identify different entities like humans, animals, and assorted objects - Sophisticated alert system to send app notifications whenever a detected event occurs Ideal Skills & Experience: - Proficiency in Computer Vision and yolov5 - Experience in crafting alert or notification systems - Knowledge in IP camera setup and integration - Understanding of differentiating objects in image/video processing I am looking for a mindful programmer who can courageously distinguish different intruders as t...

...sets in each test sheet is stated in the Test sheet names. 4) A test sheet name starts with the number of the target variable (or target column) where we have to predict the 7 numbers. 5) Each of the 50 sheets of the workbook has a list of 9 numbers predicted by different ML models. The models used were RF - Random Forest Classifier, SVML - SVM Linear Classifier kernel, SVMR - SVM RBF Classifier kernel, SVMP – SVM poly classifier kernel and NB - Naive Bayes Classifier. 6) The actual 7 values or pattern numbers are given in the coloured cells in the top left of each sheet. Wherever these numbers have occurred in prediction results are also coloured with respective colours. 7) You may also notice something like - 388-1, 38...

...sets in each test sheet is stated in the Test sheet names. 4) A test sheet name starts with the number of the target variable (or target column) where we have to predict the 7 numbers. 5) Each of the 50 sheets of the workbook has a list of 9 numbers predicted by different ML models. The models used were RF - Random Forest Classifier, SVML - SVM Linear Classifier kernel, SVMR - SVM RBF Classifier kernel, SVMP – SVM poly classifier kernel and NB - Naive Bayes Classifier. 6) The actual 7 values or pattern numbers are given in the coloured cells in the top left of each sheet. Wherever these numbers have occurred in prediction results are also coloured with respective colours. 7) You may also notice something like - 388-1, 38...

...sets in each test sheet is stated in the Test sheet names. 4) A test sheet name starts with the number of the target variable (or target column) where we have to predict the 7 numbers. 5) Each of the 50 sheets of the workbook has a list of 9 numbers predicted by different ML models. The models used were RF - Random Forest Classifier, SVML - SVM Linear Classifier kernel, SVMR - SVM RBF Classifier kernel, SVMP – SVM poly classifier kernel and NB - Naive Bayes Classifier. 6) The actual 7 values or pattern numbers are given in the coloured cells in the top left of each sheet. Wherever these numbers have occurred in prediction results are also coloured with respective colours. 7) You may also notice something like - 388-1, 38...

...we filled this job position for over 2 years. 1) Data Analytics with Python Course: Content (introduction to python, data wrangling with pandas, descriptive statistics with python, data visualization with seaborn, t-test/anova /chi-square tests with python, correlation, regression with statsmodel) 2) Machine Learning with Python Course: Content classification(dcision trees, knn, naive bayes, logReg, classifier evaluation) regression (linear regression with normal equation, stochastic gradient descent, polynomial regression, ridge regression, lasso regression, elastic net, early stopping, regression trees) advanced supervised learning concepts (feature extraction, imbalanced data ,cross-validation, hyperparameter tuning with grid and random search, overfitting/und...

...sets in each test sheet is stated in the Test sheet names. 4) A test sheet name starts with the number of the target variable (or target column) where we have to predict the 7 numbers. 5) Each of the 50 sheets of the workbook has a list of 9 numbers predicted by different ML models. The models used were RF - Random Forest Classifier, SVML - SVM Linear Classifier kernel, SVMR - SVM RBF Classifier kernel, SVMP – SVM poly classifier kernel and NB - Naive Bayes Classifier. 6) The actual 7 values or pattern numbers are given in the coloured cells in the top left of each sheet. Wherever these numbers have occurred in prediction results are also coloured with respective colours. 7) You may also notice something like - 388-1, 38...

...skills Deliverables: - Converting raw data into useful information using Hive and Visualizing the results of queries into the graphical representations. - Conduct advanced analytics using analytical methods like descriptive statistics, correlation, hypothesis testing, density estimation in PySpark. - Design and build a binary classifier over the datase and present findings into both numerical and graphical representations. - Apply a single/multi-class classifier to classify data into classes and evaluate and visualize accuracy and performance. - Provide project documentation include all queries, algorithms and models and comprehensive data analytics report presenting related numerical and graphical analytical results. Freelancers having extensive experience in the a...

I'm seeking an experienced AI/ML expert to develop a machine learning model specifically for classifying diabetic retinopathy using image data. This project aims to leverage the potential of AI in medical diagnostics, with a focus on enhancing the precision and reliability of diabetic retinopathy identification. ### Ideal Skills and Experience: - Proficient in AI and ML technologies, with a strong emphasis on image processing and classification algorithms. - Extensive experience with Python, TensorFlow, Keras, or similar frameworks. - Background in medical imaging, computer vision, or related fields. - Familiarity with dataset augmentation and handling large volumes of image data. - Proven track record of developing high-accuracy ML models, preferably in healthcare. ### Requirements...

Do zrealizowania dwa projekty z moimi własnymi bazami danych w KNIME: 1. KNIME REGRESJA LINIOWA Zbuduj model regresji liniowej dla danych AmesHousing. Wypróbuj różne kombinacje predyktorów (zmienych niezależnych) i znajdź taką, która daje najlepsze R2 adjusted. Przeprowadź kilka prób dla różnych podziałów danych na zbiór treningo...podziałów danych na zbiór treningowy i testowy i zapisuj wyniki w pliku excela (wyjściem węzła Numeric Scorer ma być Excel writer). Sprawdź jak wynik się zmieni jeśli zastosujemy węzeł regresji wielomianowej. KLASYFIKACJA Zbuduj Knime workflow, który zastosuje do danych ClevelandHeartData następujące klasyfikatory: Logistic regression Decision tree Random forest Tree ensemble le...

As we discussed: 1. I would like to explain algorithm that you have developed and compare it with the last algorithm before the enhancing . 2. also, I need to write one real case study to evaluate our result by using this algorithm. 3. Write one page at least as a problem statement part , you should mention stacking classifier and hybrid stacking by looking at an academic paper in last 3 years to find the gap and what is the weakness in there algorithm.

analysis, 3-4 days.............

I'm urgently seeking an expert in deep learning to develop an AI system capable of classifying images efficiently. The focus will primarily lie in adapting current methodologies in image classification to suit a range of potential applications. Given the variety of images it may encounter, flexibility and robustness are key. **Requirements:** - Proven experience in deep learning, specifically image classification. - Familiarity with various image types and the challenges associated with each. - Ability to deliver a working prototype urgently. **Ideal Skills:** - Proficiency in Python and deep learning libraries (e.g., TensorFlow, PyTorch). - Previous work with diverse image datasets. - Strong communication skills and able to meet tight deadlines. **Project Goals:** - Develop a scal...

I need you to choose any two distinct objects of your choice Collect at least ten photos of each object The classifier would go over each image and draw a frame around the object present in the image and then write the correct label on it It would do this for all of the collected photos Check the attached photo, I just want the collected images to have only one unique object in it and draw single frame and label it The python code should be in google colab I do not want something advanced

Urgently seeking a highly skilled WordPress developer available on February 2, 2024, and potentially over the weekend. The project involves complex WordPress tasks, including speed optimization, addressing Linux issues, and resolving core WordPress challenges. Key Require...preferably the following weekend. Advanced WordPress Skills: The candidate should have expert skills in WordPress to tackle complex technical issues. Proven track record in significantly improving WordPress site performance. Work must be done on VM/Remote machines. We do not grant admin access for local work. This is a firm policy. Requests for admin access will be viewed as unprofessional and naive. We believe in professional trust but not in handing over sensitive access to new acquaintances from a freelance...

I require a skilled freelancer to build an AI-powered machine learning model for classifying 2D images of heavy vehicles. The ideal candidate will have experience in Python programming, specifically with libraries relevant to machine learning and AI like TensorFlow or PyTorch. Key project requirements: - Develop and train a robust machine learning model. - Classify 2D images of heavy vehicles efficiently. - Work with labeled image files (JPEG, PNG, etc.) for model training. - The final model should accurately distinguish images of heavy vehicles. - Ensure the model is scalable for potentially increasing category numbers in the future. Key skills needed: - Proficiency in Python and machine learning libraries. - Experience with Convolutional Neural Networks (CNNs). - Knowledge of data prep...

I'm seeking an expert in Python to develop a sophisticated classifier that can distinguish between blurred and non-blurred images with precision. The classifier needs to detect various blurring techniques with high accuracy, especially: - Gaussian blur - Motion blur The goal is for the classifier to achieve above 90% accuracy. To successfully bid on this project, you'll need: - Proficiency in Python - Experience with image processing - Knowledge in using machine learning libraries (e.g., TensorFlow, Keras) - Understanding of computer vision and image classification algorithms If you can demonstrate past projects where you've achieved similar results, that would greatly enhance your proposal. I'm looking forward to working with a detail-oriented ...

Seeking an AI expert to develop a cutting-edge model capable of classifying environments through audio analysis. Here's what I need: - Fluent with Neural Networks: Your proficiency with neural networks should be evident, as they are crucial to the project's success. - Experience with Audio Data: You should be adept at processing and analyzing audio recordings, extracting meaningful patterns that will aid in accurate environment classification. - Commitment to Accuracy: The model must perform at an advanced level, showcasing high accuracy and precision in its classification results. Ideal Candidate Skills: - Neural network implementation - Audio processing and feature extraction - Machine learning optimization - Keen eye for detail and accuracy - Experience with high-accuracy mo...

Mengklasifikasikan data menggunakan python dengan algoritma naive bayes. contoh flow: Frontend mengirim data -> (Klasifikasi) data di python -> passing balik ke frontend. (hanya mengerjakan di klasifikasi) contoh data yang dikirim dari frontend: [51, 68, 25, 8, 29, 22] hasil yang diharapkan: Baik/Sedang/Tidak Sehat/Sangat Tidak Sehat/Berbahaya perhitungan data berdasarkan dari data csv dibawah, terimakasih.

I'm looking for a talented Python programmer who can create a stack ensemble using multiple machine learning algorithms. The successful freelancer will: - Develop a stack ensemble using: - Random Forest (RF) - Support Vector Machine (SVM) - Logistic Regression (LR) - K Nearest Neighbor (KNN) - Naive Bayes - Compare the output through voting with a trained Artificial Neural Network (ANN). I am seeking a freelancer who has a deep understanding of these algorithms, can showcase their ability to deploy them effectively and explain their approach in a detailed project proposal. The proposed solution should provide comprehensive code implementation and commentary explaining the methods used and their effectiveness. Dataset Utilization: - The KDD-NSL dataset - The...

Require screen sharing video call 1 hr for now - introduction how to & setup, etc For this project, the goal is to create an image recognition system capable of identifying whether an image contains a cat or a dog. I'm inclined towards the implementation of deep learning algorithms, given their efficacy in image classification tasks. The chosen algorithm should proficiently sort images into either 'cat' or 'dog', enhancing the accuracy level is a priority. Required Skills and Experience: - Proficiency in Python - Solid understanding of deep learning algorithms - Experience in image classification tasks - Familiarity with popular deep learning frameworks (TensorFlow, PyTorch, Keras, etc.) as the client has left the choice of framework open-ended.

...basic tweaks. It’s an e-commerce site rich in content, demanding optimizations that maintain high performance and smooth user experience. Requirements: Proven track record in significantly improving WordPress site performance. Work must be done on VM/Remote machines. We do not grant admin access for local work. This is a firm policy. Requests for admin access will be viewed as unprofessional and naive. We believe in professional trust but not in handing over sensitive access to new acquaintances from a freelancer website. The focus is not only on achieving high PageSpeed scores but also on ensuring the site remains robust, user-friendly, and visually intact. Project Pricing and Completion: This project is on a fixed-price basis. Your proposal should include your rate for ...

Require screen sharing video call 1 hr for now - introduction how to & setup, etc For this project, the goal is to create an image recognition system capable of identifying whether an image contains a cat or a dog. I'm inclined towards the implementation of deep learning algorithms, given their efficacy in image classification tasks. The chosen algorithm should proficiently sort images into either 'cat' or 'dog', enhancing the accuracy level is a priority. Required Skills and Experience: - Proficiency in Python - Solid understanding of deep learning algorithms - Experience in image classification tasks - Familiarity with popular deep learning frameworks (TensorFlow, PyTorch, Keras, etc.) as the client has left the choice of framework open-ended.

We need to classify various types of images after AI training. Currently we're using this library () and have replaced their images with ours and changed the categories names ...classify various types of images after AI training. Currently we're using this library () and have replaced their images with ours and changed the categories names etc. to make it fit for our needs. But as we're expanding with our categories, the predicted outcome is getting worse. It is confusing between various categories. What we need is, either a classifier built on this library or any other library doesn't matter, to which we can feed our categories and training dataset and it produces accurate results when predicting

...data. Develop a plan as to how you might transform the data to make it useable. • Develop a plan as to which artificial intelligence techniques you might use and what sorts of potential observations these can lead to, and how you will evaluate these. You must use models, these are: perceptron, decision trees, linear regression, support vector machines, random forest, k-nearest neighbour, naïve Bayes, neural networks as well as unsupervised techniques k-means and GMM, and principal component analysis. Most supervised models have both classification and regression variants. You are encouraged to work with neural networks. An additional technique from outside the taught module content might be applied for comparison purposes, if this is done it should be clearly indicated ...

We need to classify various types of images after AI training. Currently we're using this library () and have replaced their images with ours and changed the categories names ...classify various types of images after AI training. Currently we're using this library () and have replaced their images with ours and changed the categories names etc. to make it fit for our needs. But as we're expanding with our categories, the predicted outcome is getting worse. It is confusing between various categories. What we need is, either a classifier built on this library or any other library doesn't matter, to which we can feed our categories and training dataset and it produces accurate results when predicting

I'm seeking an experienced developer to deploy and configure the Amazon AI sample code...has code for this) 3) Deploy the web application to AWS (sample has code for this) 4) Configure AWS api and cloud related APIs and keys into database configuration or file 5) Add user authentication to app for security.. 6) Add final code to github - For this job, knowledge and experience in AI technology and AWS deployment, particularly with Amazon JupyterNotebooks, Web app, S3, XGBoost classifier using SageMaker are ideal. Proficiency in handling user uploaded content and image/video analysis an effective way is essential. Understanding AWS security measures would be a significant advantage. The overall goal of the project is to create an efficient and reliable system for analyzin...

...The project will involve using an existing dataset for training the GAN model, which I already have available. The main goal of this project is to develop a GAN model that can generate realistic and diverse chest X-ray images, while also addressing the class imbalance issue and incorporating data augmentation techniques, which enhances the lung nodule detection in the images using RF and SVM as classifier. and calculate their efficiency using ROC, f1 scores.. and then transfer the same model using transfer learning to the CT images dataset and calculate efficiency in detecting lung nodules using RF and SVM If you have experience in this field and are interested in contributing to academic research, please submit your proposal. This is a great opportunity to apply your ML skills ...

Drawing a Bayes Network I am looking for a skilled freelancer who can help me with drawing a Bayes Network for my project. The purpose of the Bayes Network is to and it will be used for [insert purpose here].

I need to draw a Bayesian network (Bayes net) for the model described:

Vennligst Registrer deg eller Logg inn for å se detaljer.

The aim of this project is to implement a mul4nomial Naive Bayes model for a sen4ment analysis task using the Ro=en Tomatoes movie review dataset. This dataset is derived from the "Sen4ment Analysis on Movie Reviews" Kaggle compe44on1, that uses data from the works of Pang and Lee [1] and Socher at al. [2]. Obstacles like sentence nega4on, sarcasm, terseness, language ambiguity, and many others make this task very challenging

I am looking for a freelancer to build a classification model using Rstudio codes to identify spam vs. non-spam emails. The dataset provided is small, with less than 1000 emails. Requirements: - Proficiency in Rstudio and machine learning algorithms - Experience with building classification models - Knowledge of Naive Bayes algorithm The ideal freelancer should have expertise in Naive Bayes algorithm and be able to implement it using Rstudio codes. Additionally, the freelancer should have a good understanding of email data and spam detection techniques. I attached the code I currently have and the dataset for reference.

...is 40). The pet image labels the following way: Lower case letters Single space separating each word Correct representation of the filenames (from the 10 key-value pairs) To create the labels for pet images you will need to: Read all the files' names in the pet_image/ folder Process the filenames to create the pet image labels Format the pet image labels such that they can be matched to: The classifier function labels The dog names in dognames.txt...

The aim of this project is to implement a multinomial Naive Bayes model for a sentiment analysis using Rotten Tomatoes movie review dataset.