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Data science, which should not be mistaken for information science, is a field of study that uses scientific processes, methods, systems, and algorithms to extract insights and knowledge from various forms of data, be it structured or unstructured. It is similar to data mining and is a conception to unify machine learning, data analysis, statistics, and their related methods so as to analyze and understand the actual facts about data. Data science employs theories and techniques taken from many disciplines such as computer science, information science, statistics, and mathematics.
In a nutshell, data science can be said to be a multidisciplinary blend of algorithm development, data inference, and technology in a way to find solution to analytically complex problems. Data science is useful to anyone who wants to be a data miner.
Na podstawie 63224 ocen klienci oceniają Data Science Experts 4.87 nas na 5 gwiazdek.Dowiedz się więcej
Hi Experts, I have trained a few models, I need you to do the following: 1.) Make live predictions given a new test set. N/B: The new test set does not have the features in the training set. The features were created using preprocessing and feature engineering. 2.) Preprocess the new set to same shape as Xtest (using the existing codes) so you can do (1) above. Budget: $15 Timeline 1hr Codes attached
Need an expert for completing a project using deep learning concepts, jupyter.
Hello I need a Data Science expert using Matlab and Python Please revert if you have the required expertise.
Building alignment in an etl from end to end data lob to visualization
Genetic algorith programming c#
I am looking for an Expert in data science and business analytics
Stock Market Multitask - Multi-users iOS App STAGE 1: Price Prediction Based on Previous Days Values ======================================================= Will be an iOS for 5 users. Using historical data from previous dates, from Yahoo Finance, predict the next 5 DAYS Max/Min value of any "Stock Symbol" ("SS"). There will be a list of "SS" of interest for each user. You have to provide predictions for all of them. Samples values for some "SS" of interest are in pictures A, B, C & D. Values shown are Minimum, Maximum & Closing: - USD/MXN - $19.7192 / $19.8690 / $19.8042 Historical values can be found here: - USD/MXN - STAGE 2: Handle yours, and another 5-7 predictions ================================================== Along with yo...
This is a project on big data analytics and Machine learning on cloud. Deadline is on the 18th of December
writing about the relation between number of features and number of instances? Two conclusions can safely be drawn from this study. First, the behavior of the optimal-feature-size relative to the sample size depends strongly on the classifier and the feature-label distribution. An immediate corollary is that one should be wary of rules-of-thumb generalized from specific cases. Second, the performance of a designed classifier can be greatly influenced by the number of features and therefore one should attempt to use a number close to the optimal number. This means that it can be useful to refer to a database of optimal-feature-size curves to choose a feature size, even if this means making a necessarily very coarse approximation of the distribution model from the data—even perhap...
I need somebody who can help me to build a machine learning model, The project is going to help in practical implementation, So I need somebody who has good knowledge and experience in machine learning.
- Understand SoftMax Regression - Understand Linear Regression, Logistic Regression Calculations - Neural Network Calculations - KN-MEANS - LogLoss - Decision Trees - Naive Bayes Classification - Evolutionary Computing - Genetic Algorithms - Python Programming and Tensorflow - Convolutional Neural Networks - SoftMax Classifier
I am building a Siamese Network and need assistance with some few tweaks. This is a small request as most of the development is already done.
Build A Customer 360 View: Centralizing customer data view Multi-Channel Data Collection. Data ingestion ERP, POS, Loyalty Program, Web Analytics, CRM, Channel Response data, Online behavior and purchase data, Customer Feedback/survey data Normalize data upstream from other sources Integrate customer data from multiple sources via API, WebHook A/B testing capacities to check campaign effectiveness (A vs B) Real time Customer Segmentation Behavioral Segmentation ( Clustering) Micro Segmentation based on rules/lists Propensity Models Lookalike Profiling Cross Sell/ Up Sell Models CLTV Modeling Churn Model Channel Propensity Arabic Support Integrated with Punch KPIs =========================== What Customers Do 1- Who are our Customers ( Customer Attribution )-DB & Number of Custome...
Here is a data set, please could you complete the following tasks: • Identify the incorrect or inconsistent data? • Present your findings visually • Explain why you feel the data is incorrect or inconsistent? • Explain how you would go about cleansing the data? • What would you put in place to prevent this data from being incorrect next time? You will be expected to talk through your thought process and present your findings. You will be given 20 minutes to present.
Here is a data set, please could you complete the following tasks: • Identify the incorrect or inconsistent data? • Present your findings visually • Explain why you feel the data is incorrect or inconsistent? • Explain how you would go about cleansing the data? • What would you put in place to prevent this data from being incorrect next time? You will be expected to talk through your thought process and present your findings. You will be given 20 minutes to present.
System is setup to upload - working Create heatmap - working Example of ui (Enclosed ) - done Deliver 4 images of similar type based on reverse lookup Error seen File "/home/ec2-user/site/", line 1715, in covercompareresults heatmap = ('.')[0]+'' titles, images = query('/home/ec2-user/site/static/uploads/cover_uploads/'+) print(titles[0][1]) isbn1 = titles[0][1] title1 = titles[0][0]Open an interactive python shell in this frame img1 = images[isbn1] isbn2 = titles[1][1] title2 = titles[1][0] IndexError: list index out of range Architecture setup in AWS for EC2 application and web (Enclosed section of and example code) Architecture setup in resize files and create pickle db for quic...
I need someone to evaluate my resume from a technical angle and give an expert opinion based on that or a reference. Someone that has done some great work in cybersecurity or academics would be a great fit. US Applicants needed.
Please redo the analysis chapter by analyzing the attached NVIVO files. . Explain how I coded by using the data or the interview 2. How to decide on the code 3. Coded systematically see certain Partain using code to category? identify themes ? describe how you coded (is it theme coded ) how to decide on the code number of codes? How did I go about coding Why coded that way 4. With the data analysed from Nvivo how did you develop the theory. Step by step and where is the theory developed ? 5. the systematic approach to conduct the framing process results presentation 7. Frames results Also present all references coded 8. Relating the frame results to the participants attributes 9. Participants contributing to the frame perspectives the first frame results to the participants attr...
El proyecto es un poco grande, solo para personas serias y con suporte en el futuro ya que se haran modificaciones a la app, consiste en costruir un app de 4 modules -Iniciar secion por medio de usuario y contrasenia -4 modulos principales: Proveedores, Bancos, Gastos y Corte -Cada uno debera guardar datos en objetos para luego ser manipulados con graficas -Contara con una lista de proveedores que tendra una barra buscadora Horas prodedio de trabajo: 7-15hrs para la gente que este dispuesta a trabajar estare contactandolos, ver documento de PPT tiene que darle presentacion (F5) para entender el proyecto
