Search the world's information, including webpages, images, videos and more. To see examples of using NARX networks being applied in open-loop form, closed-loop form and open/closed-loop multistep prediction see Multistep Neural Network Prediction. We predicts whether there is rainfall at a location, based on (processed) infrared satellite image information. code exam date exam time1 fluid mechanics 3007 friday, december 16,. In this hands-on course, you will learn how to build predictive models with Python. Though first attempted in the 1920s, it was not until the advent of computer simulation in the 1950s that numerical weather predictions produced realistic results. Specifically are there any python libraries/open-source-code specific for use case, which I can build upon. Using the chosen model in practice can pose challenges, including data transformations and storing the model parameters on disk. Princeton, New Jersey Oct, 2009 The eighth workshop on decadal climate variability. That seems pretty naive! We advance by repeatedly failing and learning rather than by only promoting our success. There is a possibility to receive a central district of the city/town with its own parameters (geographic coordinates/id/name) in API response. Python and Numpy can be used to perform quick analyses on large datasets, which is especially important for weather and climate prediction and monitoring. A description of the stations for each state is available by FTP. Prediction with Python So this is a good chunk of code, and I've already loaded that in there. Lab Report Answer the questions below. Download Code. It focuses on fundamental concepts and I will focus on using these concepts in solving a problem end-to-end along with codes in Python. 2 “measuring and prediction the major source of particulate matter and health impacts by using computer models or instrumentations”,(a) summarize different methods of measuring and prediction the major source of air pollutions in certain areas,(b)why it is important to the human health impact ?. Since I am going to have a 5-day trip to Sapporo, Hokkaido, Japan at the end of August, I would like to have a weather forecast for my trip. The statement was made moments after the Foxes secured a return to the Premier League and after. Average weather climate keyword after analyzing the system lists the list of keywords related and the list of websites with related content, in addition you can see which keywords most interested customers on the this website. rDock is mainly written in C++ and accessory scripts and programs are written in C++, perl or python languages. Recently searched. Now that you have considered the professional skills within the SFIA framework, you should be able to assess the skills that you have used and demonstrated in your internship. NOTE : You can pass one or more iterable to the map() function. Weather: 06. If you run genderPredictor. Search: Search. py --company AAPL Features for Stock Price Prediction. All of these factors combine to make Python a terrific alternative to C++ and Java as a general purpose programming language. Watch Queue Queue. Saikumar has 7 jobs listed on their profile. Tech in Data Analytics, Strong at Statistical concepts, Predictive. This may be used as the basis for an operational large-scale fluvial-flood prediction tool by the Met Office. How do we predict the weather for day 2 given pi(1) and the transition kernel q? From the transition kernel, we can see that the probability of day 2 being sunny is. See how to submit a training job using Python 3. The analysis was completed using data from the Wunderground weather website, Python, specifically the Pandas and Seaborn libraries. There are two outputs coming out of R that I'm not seeing how. So the interpreter doesn’t have to execute the. David Zierden, the state climatologist and an associate researcher at Florida State University's Center for Ocean-Atmospheric Prediction Studies, said weather patterns impacted by climate change. Erfahren Sie mehr über die Kontakte von Swaroop P und über Jobs bei ähnlichen Unternehmen. Secure authentication typing patterns in java key stroke dynamic C:+91 8121953811,L:040-65511811 M:cloudtechnologiesprojects@gmail. Find the most current and reliable 14 day weather forecasts, storm alerts, reports and information for Grand Cayman, KY with The Weather Network. Everything in python is an object. I'm very confused and I don't know how to set X and y(I want the x values to be the time and y values kwh). View ZHAN CHEN’S profile on LinkedIn, the world's largest professional community. I want to fill in those missing values using the multiple regression analysis technique. I have this dataframe with this index and 1 column. Rainfall Prediction. Python for Data Analytics. Thanks to TabPy, you can create calculated fields using Python code in Tableau 10. Numerical weather prediction (NWP) uses mathematical models of the atmosphere and oceans to predict the weather based on current weather conditions. This code is currently considered 'Beta' as NIDIS performs additional testing and verification. In this post, you will discover how to develop LSTM networks in Python using the Keras deep learning library to address a demonstration time-series prediction problem. If they are carefully separated, real-time predictions can be performed quite easily for an MVP, at a quite low development cost and effort with Python/Flask, especially if, for many PoCs, it was initially developed with Scikit-learn, Tensorflow, or any other Python machine learning library. Climate Prediction Center (CPC) Climate Diagnostics Center (CDC) Week Two Forecasts (6-14 days) 6-10 Day Temperature Forecast Map; 6-10 Day Precipitation Forecast Map. Weather: 06. tak mpa all dimentions are in mm. laaraiedh@univ-rennes1. Make the predictions. An N-gram in which N=2. During the course, we will talk about the most important theoretical concepts that are essential when building predictive models for real-world problems. When I have just one input (e. 6 Create a program for storing a week's worth of rainfall data. I am working with time series data (daily data of rainfall) and have some missing data values. So the big aim here is obviously to predict the rain in the future (we'll try 6 hours). Out of 60 years of data data for few months are missing. A Practical End-to-End Machine Learning Example. This is a simple machine learning project in python to determine the annual rainfall from monthly rainfall using multi linear regression. Saikumar has 7 jobs listed on their profile. The statsmodels Python API provides functions for performing one-step and multi-step out-of-sample forecasts. Focused on predicting the probability of rainfall in different locations by using Random forest. The implementation will be specific for. In ZwAnto/toolbox: What the package does (short line). International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056. The School of Meteorology at the University of Oklahoma is the largest such program in the nation, with approximately 250 undergraduate and 90 graduate students. There are two outputs coming out of R that I'm not seeing how. Input Validation: Do not accept negative numbers for monthly rainfall figures. Python is a very popular language when it comes to data analysis and statistics. It covers various analysis and modeling techniques related to this problem. View Pooja Patel’s profile on LinkedIn, the world's largest professional community. In this article I wanted to concentrate on some basic time series analysis, and on efforts to see if there is any simple way we can improve our prediction skills and abilities in order to produce more accurate results. View Mythili Sivakumar's profile on AngelList, the startup and tech network - Developer - Seattle - Business Intelligence Engineer -. Page 1 of 1 (18 posts) talks about » movement data; Blog List. I have been messing with this program for my class for days now. We will represent this as a vector of probabilities over the three values. Tziperman, D. The code also detects when the rain sensor is dry and will trigger the motor to spin the opposite way to close the top of the tub. There is a video at the end of this post which provides the Monte Carlo simulations. Private weather companies sometimes issue customized tornado-risk predictions and alerts for their clients. However, it is important to highlight that it implicitly assumes the existence of spatial autocorrelation in the data. On the "Code Samples" page we can see the whole Python code to retrieve the current temperature in Cedar Rapids. A framework to quickly build a predictive model in under 10 minutes using Python & create a benchmark solution for data science competitions. gov : St" or Zip Code National Centers for Environmental Prediction. 0001 just to throw away the predictions that are very unlikely. In the latter part, we will translate our understanding into code and implement it on the famous 'iris' dataset for classifying flowers into one of three categories. Explore climate indices, reanalyses and satellite data and understand their application to climate model metrics. Let's say you have 2 different inputs First for X and second for Y And you want to know the percent of each input to the total It will look like this: [code]X = input() Y = input() Z = 100/(int(X)+int(Y)) print('Percent of X: '+str(X*Z)+'%') print. Here is the exercise as it appears in my book: 3. Matlab project for A Rainfall Prediction Representation using Neural Network matlab projects code TO GET THE PROJECT CODECONTACT www. I'm working with R and confirming my results in Python with the overwhelming majority of the work matching between the two quite well. Determine from the code table in Figure 1. In this file we can change the value of M and p. HoltWinters function gives the predictive result of rainfall with 80% confidence interval and 95 percent of confidence interval. It takes a two dimensional data and organises them into clusters. Abstract The contribution presents a comparison of a runoff simulated by profile method (1D) and spatially distributed method (2D). Under the Search for dropdown, select ZIP codes. We will represent this as a vector of probabilities over the three values. and ) the M. This project contains Python implementations of various climate index algorithms which provide a geographical and temporal picture of the severity of precipitation and temperature anomalies useful for climate monitoring and research. In this tutorial you will implement the k-Nearest Neighbors algorithm from scratch in Python (2. The approach you choose depends on the data that you have. Download Code. The clouds are classified into three groups, namely; nimbostratus, cumulonimbus and cumulus. Using Markov chains for prediction Suppose day 1 is rainy. For example, given the sequencefor i inthe algorithm predicts range as the next word with the highest probability as can be seen in the output of the algorithm:[ ["range", 0. 24 Hour Fronts/Precipitation. As significant as the R connection with Tableau 8. The output depends on whether k-NN is used for classification or regression:. Densities for two distinct samples are estimated and plotted. Weather: 06. Precipitation Outlook for Australia & New Zealand. Here is the exercise as it appears in my book: 3. It covers various analysis and modeling techniques related to this problem. In this article, some more social networking concepts will be illustrated with a few problems. The course is now hosted on a new TradingWithPython website, and the material has been updated and restructured. It is mostly used for finding out the relationship between variables and forecasting. Consecutive Days with Less than 0. pdf), Text File (. Our computer models simulate the climate for the next century, producing predictions of temperature, rainfall and the probability of extreme weather events. Average Rainfall Write a program that uses nested loops to collect data and calculate the. It is a very simple idea that can result in accurate forecasts on a range of time series problems. Most of the time, the equation of the model of real world data involves mathematical functions of higher degree like an exponent of. This is a post about random forests using Python. They are extracted from open source Python projects. Python's interpreted nature was also a benefit: Code ideas can easily be tested in the Python interactive shell, and lack of a compilation phase makes for a shorter edit/test cycle. fun : It is a function to which map passes each element of given iterable. Posted by iamtrask on November 15, 2015. In this post, I will provide the Python code to replicate the work and analyse information for your own city. Maps as a language Symbolization Scale Simplification/generalization Grid systems Projections. na(dt)) 2 0. This tutorial provides a step-by-step guide for predicting churn using Python. I am a former graduate research assistant and PhD student at Texas Tech University. Moreover, Python code written for a difficult task is not Python code written in vain! This post documents the prediction capabilities of Stocker, the "stock explorer" tool I developed in Python. Where can I get a sample source code for prediction with Neural Networks? Beginner coders should consider python. 68 inches, with a 95% prediction interval of (16. The Weather RSS feed enables you to get up-to-date weather information for your location. Is there a simple way to come up with a mathematical function(say, a Sine function) that fits my current data, and then I could pass new values into that function to get my prediction?. climate outlooks. I started to learn how to use Python to perform data analytical works during my after-working hours at the beginning of December. It's a relatively new machine learning strategy (it came out of Bell Labs in the 90s) and it can be used for just about anything. McIDAS-V Memory Use. We have tried to code an Easy Weather Forecast Tool in Python on a command prompt. Découvrez le profil de Swaroop P sur LinkedIn, la plus grande communauté professionnelle au monde. Rainfall Statistics Design a program that lets the user enter the total rainfall for each of 12 months into a list. Geological Survey (USGS) in a project to to determine where machine learning could assist in the area of flood prediction to improve their ability to best prepare and respond when a natural disaster occurs. load_forecast(api_key, lat, lng, time=current_time) The result is actually a request for the weather in the future in Amsterdam (by 6 hours). View Nikita Malviya’s profile on LinkedIn, the world's largest professional community. Time Series Prediction with ARIMA Models in Python, An explanation of how to leverage python libraries to quickly forecast seasonal time series data. com provide a national and local weather forecast for cities, as well as weather radar, report and hurricane coverage. Numerical weather prediction (NWP) uses mathematical models of the atmosphere and oceans to predict the weather based on current weather conditions. A GUI built using Python 2. In this tutorial, you. water volume) the network works more or less good with this code, but not when I have more than one. Watch Queue Queue. There are, however, mixed signals in rainfall projections. We'll build a system that does just that from scratch!. See the complete profile on LinkedIn and discover Saikumar’s connections and jobs at similar companies. 9, 2009 X 2 Motivation (General) Optimal usage of grid resources through “smarter” meta-scheduling Many users overestimate job requirements Reduced idle time for compute resources Save utility and energy costs Optimal resource selection for most expedient job return time. forecast = forecastio. Tashiana Osborne, a graduate student within CW3E, will be attending the 23 rd United Nations Framework Convention on Climate Change in Bonn, Germany next month. Download Open Datasets on 1000s of Projects + Share Projects on One Platform. Lab Report Answer the questions below. Government Internet Service Home page. Dynamic neural networks are good at time-series prediction. iter : It is a iterable which is to be mapped. Severe Storms & Heavy Rainfall Possible in the Plains; Critical Fire Weather Conditions for Parts of the West. Prakhar Sharma’s Activity. 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That function should be decomposed to other functions computing the score for a player and the score for a single game. is an open source Python library used by. Python Hangman Game Python Command Line IMDB Scraper Python code examples Here we link to other sites that provides Python code examples. Returns a list of the results after applying the given function to each item of a given iterable (list, tuple etc. You can save this feed in My Yahoo! or your favorite feed aggregator, or incorporate the RSS data into your own web site or client application. Drought Monitor information as well as long-range forecast precipitation, temperature, and drought information. Description. NOTE : You can pass one or more iterable to the map() function. The underlying data was released by the Met Office in the United Kingdon, which does excellent work on weather and climate forecasting. Weather Underground as part of The Weather Company, an IBM business, now offers a series of Data Packages that tap into. In this post, you will discover how to develop LSTM networks in Python using the Keras deep learning library to address a demonstration time-series prediction problem. You can view the full suite of NDFD products at the National Weather Service's Graphical Forecast page. The only thing I want from you is to edit and play with word by using synonyms and other method so it dose not look identical when I submit it. We can take advantage of the entire Python ecosystem, which is perfect for bringing machine learning to Excel. I’m lucky enough that they have a prediction for my neighbourhood but it still does not mean that if they predict 3mm that I will get all of it at my property. That was a disastrous mistake. gov > Corpus Christi, TX > NWS Corpus Christi Science and Operations Officer Page. In our rainfall prediction problem, the situation is somewhat less trivial as there is still the additional step of inferring the rainfall ‘numbers’ (the top row) from radar measurements. Python Android Weather Forecast Script I am a proud owner of an HTC Hero Android phone. RTNWSWPC: WPC's forecast for the next week (Mon to Mon) of precipitation across the CONUS. Learn the fundamentals of programming to build web apps and manipulate data. David Zierden, the state climatologist and an associate researcher at Florida State University's Center for Ocean-Atmospheric Prediction Studies, said weather patterns impacted by climate change. It asks the user for the number # of years. Download the sample from the GitHub. Process Completed Work Prediction Experiments 3 Different Platforms 1 domain To Do Testing with different domains Testing on new platforms Cross-cluster testing Model Refinement, as necessary (GPU Programming) Typical Tasks Code Inspection C++ programming (for the model) Python and BASH scripting for testing Analysis of model and/or results. Find the most current and reliable 14 day weather forecasts, storm alerts, reports and information for Grand Cayman, KY with The Weather Network. It focuses on fundamental concepts and I will focus on using these concepts in solving a problem end-to-end along with codes in Python. Découvrez le profil de ZHAN CHEN sur LinkedIn, la plus grande communauté professionnelle au monde. It obtains weekly forecast and related weather information for any. Python is a flexible and versatile programming language suitable for many use cases, including scripting, automation, data analysis, machine learning, and back-end development. A neural network is a computational system that creates predictions based on existing data. Alexandre Neto's blog; Anita Graser; Faunalia; Info Geo Blog; Ireland QGIS User Group Blog. You can search weather forecast for 5 days with data every 3 hours by city name. See the complete profile on LinkedIn and discover Jun’s connections and. The data generated is sent back to us and incorporated into the climateprediction. I am working with time series data (daily data of rainfall) and have some missing data values. I'm new to Python so every help is valuable. Story Idea: The idea of this tutorial is to provide examples of how to read sensor data with …. Discover it now. In this article, we will use Linear. ----- Starting out with Python, Third Edition, Tony Gaddis Chapter 4 Programming Challenges ----- 5. Incorporating R code into ArcGIS geoprocessing workflows. This is sampling utility implementing Latin hypercube sampling from multivariate normal, uniform &. An Open Source Solar Power Forecasting Tool Using PVLIB-Python William F. Learn the fundamentals of programming to build web apps and manipulate data. The forecast will redirect to a zone page when there was is a technical issue with the forecast page, indicated by a blue banner with the message, "The zone data will be displayed until your location has been refreshed. Studies GRASS GIS, Landscape and Visual Impact Assessment, and Geography. Key skills: • Experience using Python in a Linux environment, including committing version-controlled code to the Met Office internal code-management system. gov and Amidu. Erfahren Sie mehr über die Kontakte von Swaroop P und über Jobs bei ähnlichen Unternehmen. Matlab Rainfall Forecast Codes and Scripts Downloads Free. The Weather RSS feed enables you to get up-to-date weather information for your location. A tropical disturbance near the coast of southeastern Florida is located in an environment supporting a high chance of tropical depression formation this weekend. I've done a lot of the wrapper work for you and put it up on github. Kristofer has 7 jobs listed on their profile. It focuses on fundamental concepts and I will focus on using these concepts in solving a problem end-to-end along with codes in Python. Python Programming (COP 4045) 3 credits Prerequisite: COP 3530 with minimum grade of "C" This course is an introduction to the Python programming language with applications to practical problem solving involving data manipulation and analysis. MGET includes generic geoprocessing tools for executing R code within geoprocessing models. Storm drain calculations keyword after analyzing the system lists the list of keywords related and the list of websites with related content, in addition you can see which keywords most interested customers on the this website. question#1:::find the maximum torque that can be applied to the following concrete sections without any cracking. Geopandas Interactive Map. If you’re using Windows and are new to Python, watch this movie on how to run the following Python code. The spacecraft re-entered the Earth’s atmosphere on June 15, 2015, at 11:55 p. Checkout the gender prediction code here. However, I cannot deny the evidence that more and more people are choosing it, and there are good reasons, as their language of choice for doing research and hydrological applications. I have 365 rasters (daily_sm2rain data of a year) in. Python Android Weather Forecast Script I am a proud owner of an HTC Hero Android phone. The average January temperatures (y) and geographic latitudes (x) of 20 cities in the United States were given in the table for Exercise 3. Strategic Command’s Joint Functional Component Command for Space through the Joint Space Operations Center (JSpOC. Mathematical Problems in Engineering as the number of hidden layers in the DBN from CS C23 at Addis Ababa University. Description Usage Format Note Author(s). Are you a beginner? If yes, you can check out our latest 'Intro to Data Science' course to kickstart your journey in data science. Natural Language Processing with Python We can use natural language processing to make predictions. ----- Starting out with Python, Third Edition, Tony Gaddis Chapter 4 Programming Challenges ----- 5. It is important to exactly determine the rainfall for effective use of water resources, crop productivity and pre-planning of water structures. How To Install Python 3 and Set Up a Programming Environment on Debian 10. Inverse distance weighted interpolation is commonly used. RAINFALL CLIMATOLOGY - Yearly norms (Ga map)-- Rainfall Frequency --amounts by return period example: 24-hour amounts that occur once in 100 years; return periods by amount example: How many times per month we see 24-hour amounts of 2 inches or more. In this tutorial you will implement the k-Nearest Neighbors algorithm from scratch in Python (2. Yahoo Weather API Documentation. Extended Range Public Forecast Discussion. Kaggle-Rainfall-Prediction. I’m lucky enough that they have a prediction for my neighbourhood but it still does not mean that if they predict 3mm that I will get all of it at my property. The Climate Prediction Center's ( CPC) daily rainfall data for the entire world, 1979 - present & 50-km resolution, is one of the few high quality and long term observation-based rainfall products. This is sampling utility implementing Latin hypercube sampling from multivariate normal, uniform &. Support vector regression python time series. The course is now hosted on a new TradingWithPython website, and the material has been updated and restructured. inevitable to predict the rainfall accurately. See the complete profile on LinkedIn and discover Kristofer. Flexible Data Ingestion. i to the climate data and identify (which are the point predictions). I am working with time series data (daily data of rainfall) and have some missing data values. Access to the AccuWeather Enterprise API requires an API key. Consultez le profil complet sur LinkedIn et découvrez les relations de ZHAN, ainsi que des emplois dans des entreprises similaires. Record the number of drops of Reagent D needed to turn the solution light blue in each phase of the lab: Set-Up Observations Phase Amount of water mL or drops Amount. Average Rainfall Write a program that uses nested loops to collect data and calculate the. Strategic Command’s Joint Functional Component Command for Space through the Joint Space Operations Center (JSpOC. Then click Calculate. Other real world applications include:-Machine learning (in general)-Speech recognition and completion. Occasionally I wrote about it in my posts, also for remarking that I went in a different direction. Learn Python, a powerful language used by sites like YouTube and Dropbox. There are, however, mixed signals in rainfall projections. Python Programming for Data Processing and Climate Analysis Jules Kouatchou and Hamid Oloso Jules. What are the applications of hydrostatic solvers vs non-hydrostatic solvers in numerical weather prediction? python python-2. The Hurricane Weather Research and Forecast system (HWRF) became operational at NCEP in 2007. The project is concerned with rainfall events prediction by applying rule-based reasoning and fuzzy logic. There are currently (as of June 2017) 409 parts per million of CO2 in our atmosphere. Rainfall Prediction: A Deep Learning Approach. The underlying data was released by the Met Office in the United Kingdon, which does excellent work on weather and climate forecasting. This video is unavailable. Get a local weather forecast for over 3. 24 Hour Fronts/Precipitation. Use Weather Company Data APIs and matplotlib to generate your own weather forecast map within a python notebook. For example, given the sequencefor i inthe algorithm predicts range as the next word with the highest probability as can be seen in the output of the algorithm:[ ["range", 0. Climate scientist, UCI prof, HPC and machine learning enthusiast, fascinated by clouds and terrestrial ecosystems and their atmospheric feedback dynamics. It is mostly used for finding out the relationship between variables and forecasting. A NASA Open Government Initiative Website. abs(number) number : Can be integer, a floating point number or a complex number The abs() takes only one argument, a number whose absolute value is to be returned. You can also generate code using the MATLAB Coder app. (Midterm) What does the following Python code print out? (Note that this is a bit of a trick question and the code has what many would consider to be a flaw/bug - so read carefully). A tropical disturbance near the coast of southeastern Florida is located in an environment supporting a high chance of tropical depression formation this weekend. Python Android Weather Forecast Script I am a proud owner of an HTC Hero Android phone. [nws-changes] 20111007; NAM implementation delay-Fwd: ADMIN NOTICE NOUS41 KWBC. An N-gram in which N=2. 10 inches Rainfall learn more Consecutive Days with Less than 0. Search Weather script example. View Gopi krishna Swargam's profile on AngelList, the startup and tech network - Developer - Kansas City - Graduate student in Computer Science with 3 years of prior experience as Software. com Acknowledgments: Many of the CDAT-related slides are copied or adapted. Use a list. py') for file_name in sorted. Add the GEFS Reforecast v2 to the guidance suite as an experimental, but more homogeneous, source of guidance. python-3-5 weather-forecast weather-information python Python Updated Jan 28, 2017. and ) the M. com/58zd8b/ljl. computeScores(fixtures, predictions) that returns a list of pair (player, score). CNRFC Climate/Drought Summary - Interactive Map Interface [Back to top]. Luckily, Python3 provide statistics module, which comes with very useful functions like mean(), median(), mode() etc. The forecast rainfall of 2020 is about 24. In this post, I will provide the Python code to replicate the work and analyse information for your own city. Question Description. In this article you will learn how to make a prediction program based on natural language processing. Highly motivated to work in professional environment. This is a simple machine learning project in python to determine the annual rainfall from monthly rainfall using multi linear regression. (So if you run this code with the csv file below, it will show a dimension error). The last line's code just simply takes all of the first columns, setting them to NaNs, and then the final column is whatever i is (the forecast in this case). View ZHAN CHEN’S profile on LinkedIn, the world's largest professional community. Flexible Data Ingestion. 5 million locations from AccuWeather. gov : St" or Zip Code National Centers for Environmental Prediction. Crime Rate Prediction System using Python Introduction Criminals are nuisance for the society in all corners of world for a long time now and measures are required to eradicate crimes from our world. The clouds are classified into three groups, namely; nimbostratus, cumulonimbus and cumulus. This post is part of a series on artificial neural networks (ANN) in TensorFlow and Python. So the big aim here is obviously to predict the rain in the future (we'll try 6 hours). The Climate Data Store Application Program Interface is a service providing programmatic access to CDS data. World class weather radar plus your up to the minute weather report and current conditions. Python Android Weather Forecast Script I am a proud owner of an HTC Hero Android phone. These techniques help to produce result faster in a python code. See the complete profile on LinkedIn and discover Madhur’s connections and jobs at similar companies. Steps of the Quantitative Analysis Approach Defining the Problem: The First Step in the quantitative approach is to develop a clear, concise statement of problem. Personally worked on the graphics engine and integrating all of the components of the final game together.