Outliers työt

For an upcoming project, I am seeking an experienced Data Scientist who is particularly adept in R studio. The project involves approximately 3.5 million entries from an accounting firm's datasets and should follow the CRISP-DM framework. Responsibilities: - Data cleaning and preprocessing: Ensuring data is correctly formatted and that outliers, missing values, or inaccuracies are dealt with. - Exploratory data analysis: Extracting insights from the datasets, visualizing trends and discovering correlations. - Model development and evaluation: Carrying out predictive modeling and anomaly detection. Specifically, identifying potential financial transaction anomalies. More about the project: The goal is not predefined and can range from predictive modeling to anomaly detection...

I'm...Mileage, Year and Condition. - - Find current and historical used car price data using carsales, facebook, gumtree, autotrader, Make, model, badge - Average days on market - Lowest price, highest price, median price - How many currently for sale on each platform - Cars sold in last 12 months Filters: - Car dealers - Private sellers - Minimum and maximum kms - Location - Include/don’t include outliers - Automatic/manual transmission - Petrol/Diesel Required skills and experience: - Proven experience in data analysis and database development, specifically real-time databases. - Familiarity with automotive industry or online used car platforms is a huge advantage. - High attention to detail and a commitment to accuracy. - Ability to deliver this project ...

...Google Cloud Platform. Web Interface: A user-friendly web interface for system management will be provided, enabling model management, testing, and real-time accuracy assessments. Operational Details: Data Integration: Seamless integration with our database API to continuously retrieve and update past data. Data Handling Module: Conduct Exploratory Data Analysis (EDA). Detect and eliminate data outliers. Perform final feature engineering. Model Training Module: Aim to achieve approximately 85% accuracy in models. Train models under two architectures: DNN and LSTM for both classification and quantitative prediction tasks. Cloud Integration: Migrate the entire solution to a cloud platform. Provide APIs for ongoing training and prediction. Implement an automatic scheduling mechani...

Scenario Smart businesses in all industries use data to provide an intuitive analysis of how they can get a competitive advantage. The real estate industry heavily uses linear regression to estimate home prices, as cost of housing is currently the largest expense for most families. Additionally, in ...scatterplot: Define x and y. Which variable is useful for making predictions? Is there an association between x and y? Describe the association you see in the scatter plot. What do you see as the shape (linear or nonlinear)? If you had a 1,800 square foot house, based on the regression equation in the graph, what price would you choose to list at? Do you see any potential outliers in the scatterplot? Why do you think the outliers appeared in the scatterplot you generated? What d...

I'm seeking an expert who can employ their knowledge of statistical analysis to uncover patterns and relationships in a given dataset. Expectations: - Proficiency in statistical analysis specificall...dataset. Expectations: - Proficiency in statistical analysis specifically Partial Least Square method is a must. - Experience with data cleaning to ensure accuracy and reliability of data is essential. - Despite Python not being a traditional method for statistical analysis, I require capabilities in Python for the execution of analysis. Ideal candidates will be able to identify and work with outliers and anomalies, with an ultimate goal of predicting and forecasting future data. Experience with identifying patterns and relationships in data is crucial to effectively carry ou...

...to remove appropriate columns of data. 1.2. Apply the Low Variance Filter to remove appropriate columns of data. 1.3 Apply the High Correlation Filter to remove appropriate columns of data. Q2: Variable transform 2.1 any variables that are required to conduct the regression analysis, e.g. categorical variables to dummies. Q3: Outliers 3.1. Create boxplots of all relevant variables (i.e. numeric, non-binary) to determine outliers. 3.2. Comment on any outliers you see and deal with them appropriately. Q4: Exploratory Analysis 4.1. Correlations: Create both numeric and graphical correlations 4.2. Comment on noteworthy correlations you observe. Are these surprising? Do they make sense? Q5: Simple Linear Regression 5.1. Create a simple linear regression model u...

...Engineering Community, We are in need of developing a Software as a Service (SaaS) solution tailored to the following specifications: 1. Data Loading: The software must facilitate the loading of client information, financial transactions, and accounting transactions. 2. Transaction Grouping and Segmentation: Transactions need to be grouped and segmented based on their characteristics to identify outliers effectively. 3. Business Rules and Alerts: Incorporate 100 business rules or alert types based on either experiential knowledge or recommendations from entities such as the Financial Action Task Force (FATF) typologies. Please note that these rules will be provided to the developer by our team. 4. Alert Scoring: Develop a scoring mechanism for the alerts identified by the sy...

I seek a professional analyst to complete a univariate analysis assignment. While the type of data and the main objective of the assignment are unspecified, it is ideal that the freelancer have broad experience in analyzing both numerical and categorical data, and detecting patterns, outliers, and characteristics of distributions. Key qualities that I look for in the freelancer's application: - Broad experience in univariate analysis - Proven ability to work with different types of data - Demonstrable capabilities for detailed project proposals - Solid evidence of past work-related achievements. This listing is open to all candidates with the right skill set and experience. Be sure to detail your experience and abilities in your application, and prove your eligibility with...

...their positional coordinates with time stamps, velocity heading and other features. we just have to develop a logic and do a dummy project data of 1 path is provides below like this i have data of 80 paths of 39 planes. Core duties will include: - Analyzing and interpreting intricate aircraft sensor data - Developing reliable models for trajectory forecasting - Detecting any abnormalities or outliers in flight data - Utilizing Python for all data processing, analysis, and model development The ideal candidate should possess: - Solid experience with Python and its data processing and machine learning libraries - Proven knowledge in flight data interpretation and predictive modelling - Previous exposure on anomaly detection and flight trajectory forecasting would be advantageous...

I am seeking a specialist for an Excel Exploratory Data Analysis (EDA) pro...project will involve working with both categorical and numerical data and variables. The required skills and experience include: - Mastery in Excel for data cleaning and preprocessing - Proficient in data visualization using Excel - Familiarity with statistical analysis The primary objectives for this EDA project are: - Identification of patterns and relationships within the data - Detection of outliers or anomalies in the data - Understanding the data distribution of variables Please ensure your proposal clearly illustrates your past experience with similar projects and how you intend to achieve these objectives. Your understanding of the project requirements will play a big role in my vendor selectio...

I'm looking for a talented individual with proficiency in R, and a strong background in MIS-data analytics. Key Responsibilities: - Help with defining the specific data analysis task as I...background in MIS-data analytics. Key Responsibilities: - Help with defining the specific data analysis task as I'm currently unsure - Analyze various data types (sales, customer, financial) - Identify trends and patterns, make predictions and forecasts, and detect anomalies and outliers. Ideal Skills and Experience: - Proficiency in R - Strong background in MIS-data analytics - Excellent problem-solving skills - Ability to make sound forecasts and predictions - Expertise in spotting anomalies and outliers. Looking forward to working with someone who can help me make in...

...results. a) Descriptive Statistics: Compute basic descriptive statistics such as mean, median, standard deviation, minimum, and maximum values. This provides an initial understanding of the central tendency and variability of the dataset. b) Data Distribution: Visualize the distribution of the dataset using histograms, box plots, or kernel density plots. This helps identify any skewness, outliers, or patterns within the data. The objective of this analysis and expected results: After this detailed study and analysis, we will get the following ability/knowledge I) Be able to classify or categorise the Test Sheets into categories or classes like: a) Most friendly with SVM linear with ----test size. b) Needs removal or addition of data set to get various metric val...

...results. a) Descriptive Statistics: Compute basic descriptive statistics such as mean, median, standard deviation, minimum, and maximum values. This provides an initial understanding of the central tendency and variability of the dataset. b) Data Distribution: Visualize the distribution of the dataset using histograms, box plots, or kernel density plots. This helps identify any skewness, outliers, or patterns within the data. The objective of this analysis and expected results: After this detailed study and analysis, we will get the following ability/knowledge I) Be able to classify or categorise the Test Sheets into categories or classes like: a) Most friendly with SVM linear with ----test size. b) Needs removal or addition of data set to get various metric val...

...results. a) Descriptive Statistics: Compute basic descriptive statistics such as mean, median, standard deviation, minimum, and maximum values. This provides an initial understanding of the central tendency and variability of the dataset. b) Data Distribution: Visualize the distribution of the dataset using histograms, box plots, or kernel density plots. This helps identify any skewness, outliers, or patterns within the data. The objective of this analysis and expected results: After this detailed study and analysis, we will get the following ability/knowledge I) Be able to classify or categorise the Test Sheets into categories or classes like: a) Most friendly with SVM linear with ----test size. b) Needs removal or addition of data set to get various metric val...

...results. a) Descriptive Statistics: Compute basic descriptive statistics such as mean, median, standard deviation, minimum, and maximum values. This provides an initial understanding of the central tendency and variability of the dataset. b) Data Distribution: Visualize the distribution of the dataset using histograms, box plots, or kernel density plots. This helps identify any skewness, outliers, or patterns within the data. The objective of this analysis and expected results: After this detailed study and analysis, we will get the following ability/knowledge I) Be able to classify or categorise the Test Sheets into categories or classes like: a) Most friendly with SVM linear with ----test size. b) Needs removal or addition of data set to get various metric val...

design a plan for collecting and processing nucleic acids. Answer the following questions using two or more sources in APA format for this 3-5 page paper. Outline what evidence you would need to ...need to determine the answer to your question. Identify two different Biotechnological methods that could be used to solve the problem. Discuss the science behind each method. Pick the best method for answering your experimental question. State why you chose that method and why you believe it is the best method that can be used to answer your experimental question. Outline any ethical concerns or outliers. Work out the problem by describing your experimental design and stating all probably results. Defend the answer to your question. IT MUST BE ON THE SCENARIO I ALREADY MADE IN THE ATT...

...formatting features and capabilities. **Core Requirements:** - **Dynamic Filtering:** Create an interface where the displayed data can adapt to user input or selections, providing a highly interactive experience. - **Conditional Formatting:** Implement rules that change the appearance of the data (such as color coding) based on its content, making it easier for users to understand patterns and outliers at a glance. **Purpose & Audience:** - The primary aim is to display data to the general public. Hence, the solution needs to be intuitive, user-friendly, and accessible to individuals with varying degrees of technical proficiency. **Skills and Experience Ideal for This Job:** - Proficiency in Airtable, particularly in implementing dynamic filtering and conditional...

...performing exploratory data analysis and also doing statistical modeling and forecasting. The dataset is of medium size, ranging between 1GB and 10GB, so experience managing and manipulating data of this scale is crucial. Key responsibilities shall include: - Executing data cleaning and wrangling to ensure high-quality data - Conducting exploratory data analysis to identify patterns, trends and outliers - Using statistical models to forecast future scenarios Ideally, you'll deliver the data interpretation through various visualization tools including, but not limited to, charts and graphs, maps and geographic data and infographics. Successful candidates must demonstrate prior experience in these areas, succinct communication skills and an exceptional aptitude for detai...

...research data. - Ability to communicate complex data insights in an understandable manner. - Knowledge of statistics and machine learning algorithms is a plus. **Project Scope:** - The data will be provided via email in a compressed file format. The freelancer is expected to handle the data securely and confidentially. - Perform comprehensive data analysis to identify trends, patterns, and potential outliers within the scientific dataset. - Generate insightful visualizations that effectively communicate the findings from the analysis. - Summarize the analysis in a Jupyter notebook, including the code, visualizations, and a clear, concise narrative of the insights. **Ideal Skills and Experience:** - Previous experience with data analysis projects, specifically involving scientif...

...research data. - Ability to communicate complex data insights in an understandable manner. - Knowledge of statistics and machine learning algorithms is a plus. **Project Scope:** - The data will be provided via email in a compressed file format. The freelancer is expected to handle the data securely and confidentially. - Perform comprehensive data analysis to identify trends, patterns, and potential outliers within the scientific dataset. - Generate insightful visualizations that effectively communicate the findings from the analysis. - Summarize the analysis in a Jupyter notebook, including the code, visualizations, and a clear, concise narrative of the insights. **Ideal Skills and Experience:** - Previous experience with data analysis projects, specifically involving scientif...

add nse scores to evaluation add normalization to discharge data handle outliers in discharge data train with different seq_len (7,14,30) train with different kernel_size(3,5,7) update report

I'm looking for an experienced Tableau analyst to help me achieve my goals of analyzing trends and identifying patterns and outliers in my data. I don't have a specific type of data defined yet, but your expertise can guide us. Tableau is my tool of choice so familiarity with Tableau is a must. Ideal Skills and Experience: - Proficiency in Tableau's data visualization tools - Strong data analysis skills - Experience analyzing trends and identifying patterns and outliers in complex data sets - Ability to advise on data type suitable for specific needs - Excellent communication and understanding of client objectives. To do: In this Project, your goal is to perform EDA on a set of data from The World Bank, and share your insight with the (online) world. Your ...

I need a data science analyst with a Python background to assist me in analyzing trends in time series concerning hospital admissions. This project will involve the following: - Performing short-term trend analysis - Uncovering long-term trends - Identifying seasonal patterns - Spotting outliers - Help on understanding what time series model to choose if needed? The dataset we will be using will come from our own software, specifically designated for collecting this kind of information. Hence, building the analysis tool will assume a live data collected in a timely manner. The metrics available in our data are: - Admission location - Type of disease - Population data,- Length of stay Ideal candidates should have extensive experience in data science projects, a strong knowledg...

I need help crafting a marketing campaign tailored specifically for ranking senior managers utilizing the social media platform, LinkedIn, leveraging direct emails, and the construction of a microsite. The right freelancer for this project should ideally have: - A solid understanding of Software deployment issues regarding test data - A clear understanding of a ...reality with synthetic data) Let us embed your test plans into a synthetic data set Let us develop synthetic data along side your developers for better quality outcomes Our development teams bring quality code along with testable synthetic data for your application needs Let our synthetic data capabilities assure quality of your rules engines Discover if your applications can find the outliers in data with synt...

...other. 3. Date range - I want to see the dates of the earliest and latest transactions for transaction and post. Subtly include the current date at the start of your bid if you reached this part. This will ensure that the encoded dates are correct. 4. Longest & shortest duration between each transaction and post dates. This will ensure that the encoded dates are not too far apart, and any actual outliers can be identified. I might be able to help you out with the formulas. Please leave a comment if these formulas above are feasible. I have 94 of these PDFs that I may want to convert, so the project might not be a one-off thing. Unfortunately, I also have to mention that I'm price sensitive. The quality & completeness may be put into consideration but it will gene...

...a pivotal role in our advanced SEO and content strategy project. This role demands an individual who can not only analyze complex data sets but also apply this analysis to practical SEO and content development. Key Responsibilities: Data Analysis and Network Graph Theory Application: Utilize advanced mathematical techniques to analyze and interpret network graph data. Identify key patterns, outliers, and insights relevant to SEO and content strategy. SEO and Content Strategy Integration: Apply findings from network graph analysis to enhance our SEO keyword strategy. Collaborate with AI systems, including training models like ChatGPT, to identify content opportunities. Organize and present data in a way that is actionable for content writers and SEO strategists. Backlink Network...

...and would like someone to help out on a very specific part of our research. We are currently looking for someone to coherently put all the data of a file into one or two single coherent tables. The tables have to contain the vast majority of the data that we consider important and sort them through : Institution type, type of loans, region of minimum value, region of maximum value, total value, outliers, Important remark (relevant information that needs to be discussed). -The maximum budget for this is 10$/hour and the overall hours cannot be more than 6 hours, which effectively means that a maximum of 60$ will be delivered upon successful completion of the project to our standards. - Should you be selected for on the project, and extra 15$ will be delivered for the reading a...

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...visualize the proportion of missing values for each variable. B. Identify Outliers in the Dataset: Outliers can significantly impact the analysis and distort the results. You need to identify outliers in the loan application dataset. Task: Detect and identify outliers in the dataset using Excel statistical functions and features, focusing on numerical variables. Hint: Utilize Excel functions like QUARTILE, IQR, and conditional formatting to identify potential outliers. Consider applying thresholds or business rules to determine if the outliers are valid data points or require further investigation. Graph suggestion: Create box plots or scatter plots to visualize the distribution of numerical variables and highlight the outliers. C. Analy...

...significant difference (at 0.05 significance level) between games and non-game apps regarding the app revenue (logged). Briefly discuss the results. ➢ Provide the correlation matrix of the main variables. Briefly discuss the results. Exploratory Analysis ➢ Inspect the data graphically, such as visual summary statistics, check the distribution/skewness of variables, pre-check the possibility of outliers, and pre-check the relationship between the dependent and independent variables, etc. The details and types of graphs are your decision— the objective is to provide a concise yet informative inspection of the data before running the regression. You may pick up a few of the above-mentioned list of potential graphs (or other graphs), which describe various aspects of the data e...

We are looking for a python scraper expert for our financial stock's investment project. I ne...and hard worker. - Willing to learn new things. Long term work, budget is a placeholder, it can be up to more than $999 or less than $999 because it'll depends on how long you will be working with us. a. Describe your recent experience with similar projects b. Please list any certifications related to this project c. What techniques would you use to clean a data set? d. How do you deal with outliers or missing values in a dataset? e. What tools do you use for data mining and visualization? f. What is your motivation by heart to work on this project ? g. What do you know about financial stock exchange trading market ? h. Tell us why do you think a good fit to the criteria state...

You need to be an expert in TikTok Scraping & Airtable automations This tool is designed to analyze TikTok account performance by comparing average video views to significant outliers. For instance, if an account typically garners 10,000 views per video but one video spikes to 100,000 views, this tool will highlight such anomalies. Due to the large number of accounts tracked, numerous parameters are set to monitor updated average view counts and recent outliers.

I am looking for a skilled VB.net developer to draw a real...from a Data Grid View. - The purpose of the trend line is to identify outliers in the data. So Please calculate distance of each point to the line and fill in Data Grid View in third Column. Also draw a thin line (or in different color) from each point to calculated line. Requirements in this posting are complete and will not change and hence bid should be fixed. Please do not change your bid and quote your final offer only. Example Only:: -- () Ideal Skills and Experience: - Strong proficiency in VB.net - Experience in data analysis and trend line drawing - Knowledge of linear regression algorithms - Ability to work with data sets and identify outliers accurately

...Marketing: Develop and execute email campaigns to nurture leads and encourage conversions. Goals and Metrics: - Increase sales revenue: Implement strategies to optimize conversions and drive sales growth. Target Audience: - Consumers (B2C): Focus on reaching and engaging with the target consumer audience - Unique fashion seekers, streetwear enthusiasts, hyped label followers, high snob followers, Outliers, Rebels, Music factions, indie, independent etc. Skills and Experience: - Proven experience in performance marketing with a focus on generating sales revenue. - Strong understanding of consumer (B2C) marketing and the ability to create compelling campaigns. - Proficiency in utilizing social media, search engine marketing, and email marketing channels. - Analytical mindset wit...

I am looking for a freelancer who can draw a best fit circle using a set of XY coordinates. Number of XY coordinates: 5-10, Type is "Double" Data Grid View will allow user input of points, and resultant circle to be shown in a Picture Box. Purpose of the best fit circle: Data Analysis and Identify the outliers. Specific requirements: I need the freelancer to provide me with the circle center coordinates and its radius. Ideal skills and experience for the job: - Proficiency in drawing best fit circles using XY coordinates - Strong understanding of data analysis techniques - Ability to accurately calculate circle center coordinates and radius If you have experience in data analysis and can accurately draw a best

I am looking for a skilled VB.net developer to draw a real time trend line from X Y Coordinates. The trend line needed is a linear one. - The data points shall be of type "Double" for the trend line and need to be taken from a Data Grid...to draw a real time trend line from X Y Coordinates. The trend line needed is a linear one. - The data points shall be of type "Double" for the trend line and need to be taken from a Data Grid View. - The purpose of the trend line is to identify outliers in the data. () Ideal Skills and Experience: - Strong proficiency in VB.net - Experience in data analysis and trend line drawing - Knowledge of linear regression algorithms - Ability to work with data sets and identify outliers accurately

...Description: I am seeking a skilled R programmer to assist me with a project that involves data cleaning and preprocessing, statistical analysis and modeling, as well as data visualization and reporting. The ideal candidate should have experience and expertise in the following areas: Data Cleaning and Preprocessing: - Proficiency in data cleaning techniques using R - Experience in handling missing data, outliers, and data transformation - Familiarity with data imputation methods and feature engineering Statistical Analysis and Modeling: - Strong knowledge of statistical concepts and methods - Experience in conducting hypothesis testing, correlation analysis, and regression analysis - Proficiency in implementing various statistical models in R, such as linear regression, logisti...

...5. Top Selling Countries (Using Spark) 6. Item Costs (Using Spark) 7. Sales Yearwise (Using PySpark) 8. Orders per Item (Using PySpark) 9. Country with Highest Sales (Using PySpark) 10. Customer Segmentation: Use clustering algorithms to identify different customer segments. 11. Time Series Forecasting: Predict future sales using ARIMA or LSTM. 12. Anomaly Detection: Identify any anomalies or outliers that could indicate fraudulent activity. 13. Association Rule Mining: Find associations between different products in the data (Using Spark). 14. Price Elasticity: Understand how the demand for a product changes with a change in its price (Using PySpark). 15. Correlation Between Priority and Profit: Analyze if 'Order Priority' has any correlation with 'Total Profit�...

...5. Top Selling Countries (Using Spark) 6. Item Costs (Using Spark) 7. Sales Yearwise (Using PySpark) 8. Orders per Item (Using PySpark) 9. Country with Highest Sales (Using PySpark) 10. Customer Segmentation: Use clustering algorithms to identify different customer segments. 11. Time Series Forecasting: Predict future sales using ARIMA or LSTM. 12. Anomaly Detection: Identify any anomalies or outliers that could indicate fraudulent activity. 13. Association Rule Mining: Find associations between different products in the data (Using Spark). 14. Price Elasticity: Understand how the demand for a product changes with a change in its price (Using PySpark). 15. Correlation Between Priority and Profit: Analyze if 'Order Priority' has any correlation with 'Total Profit�...

I am looking to have some Exploratory Data Analysis, Impact of Outliers and Transformations, and Data Cleaning and Feature Engineering done. I'm open to suggestions regarding potential outliers and transformations, as I'm not sure what type of dataset will be used for the analysis. The deliverables for this project will need to include conducting an exploratory data analysis, identifying outliers and performing transformations as needed, and doing feature engineering and data cleaning to enable effective data exploration. The deliverables should also include accurate visual representations of the data to ensure accurate findings. Please take a look at the pdf file as this explains the assignment. This is a great opportunity for someone with knowledge of da...

I am looking for someone to help me carry out rule mining on a medium-sized dataset of 1000-10000 records. This project is for personal use only. My main aim in Rule Mining is to identify patterns and generate rules which I can use for predictive analysis and understanding of outliers in the data. I need someone who has experience and expertise in Rule Mining, and who can process my dataset quickly and efficiently. Also one part of this is to use auto-encoders. I expect person knowledge of both auto-encoders and rule mining.

...access control to differentiate between administrative and regular user capabilities. Dashboard Users can view a summary of their past analyses. Access to saved data sets and configurations. Profile management options, including password change and account deletion. Data Upload and Management Support for uploading data in CSV, Excel, and SPSS formats. Data validation to check for missing values, outliers, and format inconsistencies. Metadata management to store additional information about the data sets. Statistical Analysis Integration of open-source Python packages for SEM and MCDM. MCDM Analysis SEM Analysis Result Presentation Results will be presented in graphical formats such as scatter plots and path diagrams. Option to download reports in PDF and Word formats. Subscri...

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seeking an experienced data analyst to do a quantitative and qualitative analysis of the collected data. Responsibilities: Data Preparation: Clean and organize datasets for analysis. Handle missing data and identify potential outliers. Quantitative Analysis: Conduct correlation and regression analysis to examine the relationship between population growth and various environmental sustainability indicators. Utilize statistical software (preferably Stata) for data analysis. Qualitative Analysis: coding and categorizing qualitative data from interviews, surveys, and policy documents. Conduct thematic analysis to identify key themes and patterns. Reporting: Create clear and concise reports summarizing the analysis results, including visualizations and interpretations. Key Requ...

...who subscribe to term deposits ("yes") and those who do not ("no"). 2. Dataset: I will provide you with the "Bank Marketing" dataset, which includes various client attributes (e.g., age, job, marital status) and campaign-related information (e.g., contact type, last contact duration). 3. Scope of Work: Data Preprocessing: Clean, preprocess, and explore the dataset to handle missing values and outliers if any. Feature Engineering: Create relevant features or encode categorical variables as needed. Model Selection: Experiment with different machine learning algorithms, including but not limited to logistic regression, decision trees, random forests, and gradient boosting. Model Training: Train and optimize the selected model(s) using appropriate tech...

...Description: I am seeking a statistician or data analyst with proficiency in SPSS to conduct a comprehensive analysis on a questionnaire related to football coaching in Malaysia's Professional League. Details of the task include: 1. Data Entry: - Input the raw data from the questionnaire into SPSS, ensuring accuracy and integrity of the data. 2. Data Cleaning: - Check for missing values, outliers, and any other discrepancies that might affect the analysis. - Offer recommendations on how to handle any issues found. 3. Descriptive Statistics: - Provide frequency distributions, means, standard deviations, and other relevant statistics for each question. 4. Inferential Statistics: - Based on the nature of the data and the hypotheses (to be shared later), con...

As a data scientist, I am looking for an expert in normalizing flow algorithms in order to develop a project for outlier detection and make it better by improving the attention mechanism. I will provide the data for this project, which is image data and it is already labeled for training purposes. Therefore, the freelancer should ha...expert in normalizing flow algorithms in order to develop a project for outlier detection and make it better by improving the attention mechanism. I will provide the data for this project, which is image data and it is already labeled for training purposes. Therefore, the freelancer should have an expert level understanding of normalizing flow algorithms. The goal of this project is to identify outliers using normalizing flow to better understand the i...

BOOK: OUTLIERS: THE STORY OF SUCCESS BY MALCOLM GLADWELL 1: Please read the chapters 1 and 2 of the book. Summarize the key learning of each chapter in a few sentences. 2: Think of 4 examples (mentioned in the book or otherwise) arising from the above learning(s) that may relate to any part of the class. Each example may relate to a different point or to the same point. For example, you may find that the key learning relates to something we discussed about competition and/or something we discussed in branding. 3: Explain how and why these examples connect to the topic(s) you think they relate to. Write in a way that someone who has not read the book can understand the key point and how the examples relate to our class. For example, in his book David and Goliath, Gladwell...

BOOK: OUTLIERS: THE STORY OF SUCCESS BY MALCOLM GLADWELL 1: Please read the chapters 1 and 2 of the book. Summarize the key learning of each chapter in a few sentences. 2: Think of 4 examples (mentioned in the book or otherwise) arising from the above learning(s) that may relate to any part of the class. Each example may relate to a different point or to the same point. For example, you may find that the key learning relates to something we discussed about competition and/or something we discussed in branding. 3: Explain how and why these examples connect to the topic(s) you think they relate to. Write in a way that someone who has not read the book can understand the key point and how the examples relate to our class. For example, in his book David and Goliath, Gladwell...