Boston Housing Price Prediction Ml Project

How I made $500k with machine learning and HFT (high frequency trading) This post will detail what I did to make approx. Shop new & used cars, research & compare models, find local dealers/sellers, calculate payments, value your car, sell/trade in your car & more at Cars. Housing Market Synopsis: The US real estate market continues to grow with rising prices, new construction, supported by a strengthening domestic economy. I will discuss my previous use of the Boston Housing Data Set and I will suggest methods for incorporating this new data set as a final project in an undergraduate regression course. 1728 Fax: 206. Launched by the U. It consists of 506 observations of 14 variables which represent housing parameters taken in the suburbs of Boston. Housing industry news, home building and construction, and housing market coverage. Our independent research, ratings, and tools are helping people across the investing ecosystem write their own financial futures. Unable to find location, please try again. In this project. The PrepCast, Presented by Project Filter | Oct. This material does not take into account your particular investment objectives, financial situations or needs and is not intended as a recommendation, offer or solicitation for the purchase or sale of any security, financial instrument, or strategy. Today's technology marketer often juggles competing priorities with limited resourcing. Model Evaluation & Validation¶Project 1: Predicting Boston Housing Prices¶Machine Learning Engineer Nanodegree¶ Summary¶In this project, I evaluate the performance and predictive power of a model that has been trained and tested on data collected from homes in suburbs of Boston, Massachusetts. In 2008, oil prices reached a record high of $145/b. Windsor-Essex is predicted to lead the nation in 2018 with the highest percentage increase in housing prices, according to the annual housing market outlook report by REMAX Realty released on. This week you will build your first intelligent application that makes predictions from data. Keras is an easy-to-use and powerful library for Theano and TensorFlow that provides a high-level neural networks API to develop and evaluate deep learning models. Here we perform a simple regression analysis on the Boston housing data, exploring two types of regressors. Demand and construction activity are falling, amidst rising interest rates. Boston News, Sports, Weather, Traffic and Boston's Best. Amazing: We hit our $500,000 matching gift, and a group of generous donors has put up another $150,000 to double all donations and help us wind down our special campaign. com or start browsing below!. Search paid internships and part-time jobs to help start your career. You want to be the best real estate agent out there. 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Money orders should be made payable to charity: water and can be mailed to the address below. Morepen Lab Share Price, Morepen Lab Stock Price, Morepen Laboratories Ltd. Fidelity Investments offers Financial Planning and Advice, Retirement Plans, Wealth Management Services, Trading and Brokerage services, and a wide range of investment products including Mutual Funds, ETFs, Fixed income Bonds and CDs and much more. It consists of 506 observations of 14 variables which represent housing parameters taken in the suburbs of Boston. , Northeast, New England, and Boston-Cambridge-Newton, MA-NH metropolitan area, not seasonally adjusted. NYSERDA will award up to $10 million for the design of profitable and comfortable low-to-zero carbon emitting multifamily buildings in New York State. At this point, we can offer fair price predictions. For other international donations, we accept bank issued money orders in USD. Whether you're looking for an extra special design for your invitations, announcements, or holiday greetings, we have plenty of premium unique designs for you to choose from. Last week I completed a very amazing logistic analysis of a complex Boston housing dataset. First machine learning project — Boston House Price Prediction After having gone through some online ML courses, I realised I was still clueless as to how to start and complete a machine learning…. with Historic price charts for NSE / BSE. Innovative web and app design. Learn more. craigslist provides local classifieds and forums for jobs, housing, for sale, services, local community, and events. Inclusive ML Guide. Apache Spark is known as a fast, easy-to-use and general engine for big data processing that has built-in modules for streaming, SQL, Machine Learning (ML) and graph processing. Specify another download and cache folder for the datasets. 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Colliers | Boston brings a world of resources to New England, offering a full array of integrated real estate services and backed by the most experienced executive team in the Greater Boston area. Housing industry news, home building and construction, and housing market coverage. Shop our online collection now! Free shipping!. 3-day Forecast. com or start browsing below!. Your destination for all real estate listings and rental properties. By far this is the best web-page present currently for data science. The dataset used in this project comes from the UCI Machine Learning Repository. The data used here is loaded in sklearn's load_boston dataset and comes from the StatLib library which is maintained at Carnegie Mellon. We have helped more than 11 million small business owners since 1964. Boston-area historical tornado activity is near Massachusetts state average. A Regression Model is created taking some of the most dependent variables and adjusted to make a best possible fit. 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Our desire is to get a better. owned, developed and managed dynamic commercial, residential and mixed-use real estate in core markets across the United States. What is Linear Regression?. I have worked on the Boston housing dataset. Applied Machine Learning Project 4 Prediction of real estate property prices in Montreal´ Nissan Pow McGill University nissan. Routes, schedules, trip planner, fares, service alerts, real-time updates, and general information. More specifically you will learn:. Local residents hoping to take their horse to the Old Town Road in Wellesley may have to use GPS. Defy reality and distance with Oculus. CoStar, the world leader in commercial real estate information, has the most comprehensive database of real estate data throughout the US, Canada, UK and France. All real estate content on this site is subject to the Federal Fair Housing Act of 1968, as amended, which makes it illegal to advertise any preference, limitation or discrimination because of race, color, religion, sex, handicap, family status or national origin or an intention to make any such preference, limitation or discrimination. Stock/Share prices, Morepen Laboratories Ltd. Predict prices for houses in the area of Boston Boston house prices is a classical dataset for regression. Find the latest news, headlines, blogs and watch video about real estate, housing, mortgages, refinancing, apr and real estate markets from CNBC. Introduction My first exposure to the Boston Housing Data Set (Harrison and Rubinfeld 1978) came as a first year master's student at Iowa State. In this blog post, we feature. The USHMC website contains all the national, regional, state, metropolitan, and local data and analysis in one location. Almost anyone who owns real estate would give their second garage to know what will happen to prices in the future. Find out what you should earn with a customized salary estimate and negotiate pay with confidence. Attached is a PDF file containing all bookings at the Leon County Detention Facility from November 1, 2019. Read today’s Press Release, issued by the Department of Housing and Urban Development (HUD), for more on the topic. (MLLA), Bank of America, N. November 1st-3rd, stop by your local Virginia ABC store to save on select whiskies, vodkas, gins, cognac, rum and scotch in the 1. ca Emil Janulewicz McGill University emil. We offer a complete range of brokerage, appraisal, property management, consulting, project and construction management, and debt & equity finance services for all property types. You will also be required to use the included `visuals. Y = Boston Housing Price. Please select the appropriate activity year for the address being geocoded. Whether you are benchmarking costs for your entire portfolio or creating a detailed M&R project, CostLab provides accurate estimates in minutes. Online news and press release distribution service for small and medium-sized businesses and corporate communications. Morepen Lab Share Price, Morepen Lab Stock Price, Morepen Laboratories Ltd. Let's start with something basic - with data. AthlonSports. boston boats - craigslist CL boston boston albany, NY cape cod catskills central NJ eastern CT glens falls hartford hudson valley jersey shore long island maine new hampshire new haven new york north jersey northwest CT oneonta plattsburgh poconos rhode island south coast utica vermont western mass worcester >. See the latest Wisconsin Doppler weather radar map including areas of rain, snow and ice on AccuWeather. Therefore we can say that we have a model that fits the data to an extent. You can load the data set using: Help -> Examples -> Boston Housing. My T-Mobile Online | Access Messages, Minutes & Bills | T-Mobile. Linear regression is a statistical approach for modelling relationship between a dependent variable with a given set of independent variables. … Demand shows a strong negative relationship to price. This dataset concerns the housing prices in housing city of Boston. Tour homes and make offers with the help of local Redfin real estate agents. A professor at CSU has held the contest for 11 years. The data used here is loaded in sklearn's load_boston dataset and comes from the StatLib library which is maintained at Carnegie Mellon. Page 1 of 56 Housing Price Prediction Using Support Vector Regression A Project Report Presented to The Department of Computer Science San Jose State University. You want to be the best real estate agent out there. Don't show me this again. Price vs Crime Rate. The Boston housing data was collected in 1978 and each of the 506 entries represent aggregated data about 14 features for homes from various suburbs in Boston, Massachusetts. Why Stock Markets Continue to Rise. Installation. We take the predictions of the black box model (in our case the random forest) and train a decision tree on the original features and the predicted outcome. Syracuse University, founded in 1870 and comprised of thirteen schools and colleges, is a private research university in the heart of New York State. Then again, the problem could be you. I know I only have an associates degree in psychology. In this tutorial, you’ll learn to build machine learning models using XGBoost in python. The official website of the City of Boston. And, based on all the given information, Logistic Regression Algorithm will predict the selling price of a house. Find real estate and homes for sale today. In either case, the travel time to Earth for such material leaving the sun is 1 to 3 days. Predicting Home Prices from Various Factors Executive Summary The purpose of our project was to analyze prices of homes in Albuquerque, NM based on several variables. You may search by geography to obtain all the reports available for a particular area. Disclaimers: This article attempts to answer the question, What will the U. RERI has funded over $1 million of real estate research under the direction of some of the world's leading real estate academics and practitioners. real estate market will do in 2019? These predictions are the equivalent of an educated guess. Tour homes and make offers with the help of local Redfin real estate agents. Discover how to prepare data, fit models, and evaluate their predictions, all without writing a line of code in my new book , with 18 step-by-step tutorials and 3 projects with Weka. 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If one thing is certain, it’s that real estate in and around Boston is in high demand. The dataset used in this project comes from the UCI Machine Learning Repository. Download Open Datasets on 1000s of Projects + Share Projects on One Platform. News & World Report, where she writes consumer-focused articles about the homebuying and selling process, home improvement, tenant rights and the state of the housing market. Download the app and get a ride from a friendly driver within minutes. The key benefits of attending the 2018 BIO International Convention are access to global biotech and pharma leaders via BIO One-on-One Partnering, exposure to industry though-leaders with over 500 education sessions at your fingertips, and unparalleled networking opportunities with 16,000+ attendees from 74 countries. Real-time Predictions: Using the Boston Housing Regression Model: Real-time Predictions: Using the Boston Housing Regression Model This website uses cookies to ensure you get the best experience on our website. Metal Bulletin helps us with real-time market information crisscrossing the entire span of base metals, markets and the industry verticals. Schuler Bauer is the largest independent real estate firm in the Louisville metro area and the top company in Southern Indiana. I will discuss my previous use of the Boston Housing Data Set and I will suggest methods for incorporating this new data set as a final project in an undergraduate regression course. Housing data for 506 census tracts of Boston from the 1970 census. com for National and Regional Commercial Real Estate News, Resource Directories, Webinars, Thought Leadership and Events. He's experienced in tackling large projects and exploring new solutions for scaling. Check car prices and values when buying and selling new or used vehicles. Flexible Data Ingestion. , all of which are licensed insurance agencies and wholly-owned subsidiaries of Bank of America Corporation. BGE Home Products & Services, LLC, is not the same company as BGE, the regulated utility. Before sharing sensitive information online, make sure you’re on a. Money orders should be made payable to charity: water and can be mailed to the address below. NOAA National Weather Service National Weather Service. We'll learn the big picture of the process and a lot of small everyday tips. Let's explore fundamental machine learning terminology. Information and advice on Housing Benefit, Council Tax Support and Free School Meals. Housing Starts by State and Metro Areas Look ahead with the Home Builders Forecasts by region and type such as: State and Metro Forecasts: Includes starts forecast, Excel tables of total, single-family, and multifamily housing starts by regions, states and the top 100 metropolitan areas. The Results Are In – Institutional Investor All-American Research Poll Every year, thousands of investment professionals (nearly 4,000 to be exact) vote to determine the top equity research analysts — and firms — on Wall Street. Hi, I have trained a network using x(t) (9 rows with 96 columns - data from 1990 to 2013) and y(t) (1 row 96 columns) with ntstool. Ithaca College students collaborate with downtown festival for capstone course. Find property info from the most comprehensive source of home data online. Don't show this message again. For perspective, rates reached highs of 18. See the latest United States Doppler weather radar map including areas of rain, snow and ice on AccuWeather. Get the help you need for your children, pets, elderly parents, home and lifestyle. Use the NYC Housing Connect map above or the accessible filter for current opportunities below to find affordable housing lotteries that are currently accepting applications. We recently launched one of the first online interactive deep learning course using Keras 2. Discover what’s changed and get in touch to give us your feedback. Keras is a deep learning library that wraps the efficient numerical libraries Theano and TensorFlow. Attached is a PDF file containing all bookings at the Leon County Detention Facility from November 1, 2019. Surrogate model. How I made $500k with machine learning and HFT (high frequency trading) This post will detail what I did to make approx. Free Shipping with $50 purchase. Machine Learning Linear Regression Example :Part 1 Using Machine Learning to predict housing price Machine Learning using python and Scikit learn is packed into a course with source code for. Most experts expect a geopolitical crisis will trigger the next recession, which a majority believe will have only a moderate impact on U. Watch breaking news live or see the latest videos from programs like Good Day Philadelphia. Information and advice on Brexit Information and advice on Brexit Some. So far, I've taken a few of machine learning classes, all from Coursera, and all of them started with predicting house prices with linear regression to get us started with machine learning. Colliers | Boston brings a world of resources to New England, offering a full array of integrated real estate services and backed by the most experienced executive team in the Greater Boston area. Here is a CSV file where I have taken the adjusted daily closing price of the S&P 500 equity index from January 2000 - August 2016. Maximize the value of corporate real estate with our proprietary diagnostic, which aligns the strategies of developers, investors, and operators with business objectives and optimized footprints, as well as capital and operations-and-maintenance priorities. boston housing authority Boston Housing Authority (BHA) provides affordable housing to more than 58,000 residents in and around the City of Boston. uk to help you find and use open government data. From the Textron King Air through the Boeing 747-8, we’ve got the ADS-B Out products you need to meet the mandate now and stay on the right path for future airspace modernization. Official site includes information about The Dead, individual band members, merchandise, the Dick's Picks series, links, pictures, almanac, message board, tickets and tour information. PODS portable storage units make moving & storing easier. Usage This dataset may be used for Assessment. Metal Bulletin helps us with real-time market information crisscrossing the entire span of base metals, markets and the industry verticals. Leading provider of global metal & steel prices. We can compare the actual price of a house with our predicted price and observe the deviation. Learn about Citi credit cards that provide credit card rewards programs such as ThankYou ® Rewards, AAdvantage ® miles, or cash back!. Partner with a local real estate agent to find the home or apartment that’s right for you. Bureau Of The Census Concerning Housing In The Area Of Boston, Massachusetts. [email protected] 83 percent, according to Bankrate. On October 11, the California Association of REALTORS® (C. This material does not take into account your particular investment objectives, financial situations or needs and is not intended as a recommendation, offer or solicitation for the purchase or sale of any security, financial instrument, or strategy. , all of which are licensed insurance agencies and wholly-owned subsidiaries of Bank of America Corporation. You can only move as quickly as the slowest student, and too much time is spent explaining the basics and ensuring that everyone is on the same page (literally). (MLLA), Bank of America, N. The House Prices playground competition originally ran on Kaggle from August 2016 to February 2017. ” Disclaimer: This article includes forecasts and predictions for the California real estate market in 2019. Ravi Shankar - Medium Here is my latest live project of trying to emulate recommendation engine for movies. Search the world's information, including webpages, images, videos and more. 69 in the comparable period of 2018. Click here for more information on FFC's long range forecasts or to subscribe. Convolutional Neural Networks 5. The dataset for this project originates from the UCI Machine Learning Repository. Test Data - It will contain all the information about a house. New AncestryHealth® Understand the past, present, and future of your family’s health. Housing Starts by State and Metro Areas Look ahead with the Home Builders Forecasts by region and type such as: State and Metro Forecasts: Includes starts forecast, Excel tables of total, single-family, and multifamily housing starts by regions, states and the top 100 metropolitan areas. The school was founded in 1917 as a school of accounting and finance in Boston, Massachusetts. The all-in-one construction management software built to help you finish quality projects—safely, on time, and within budget. boston boats - craigslist CL boston boston albany, NY cape cod catskills central NJ eastern CT glens falls hartford hudson valley jersey shore long island maine new hampshire new haven new york north jersey northwest CT oneonta plattsburgh poconos rhode island south coast utica vermont western mass worcester >. edu Faculty/Staff: [NetID]@kennesaw. We also created a battery cost model that allows us to project future costs. Ravi Shankar – Medium Here is my latest live project of trying to emulate recommendation engine for movies. As mortgage rates rise, housing prices will drop to offset the higher cost to homebuyers. InsideTrack UP Takes Center Stage in Community Partnership for the Arts. Opinions, estimates, forecasts and other views contained in this document are those of Freddie Mac's Economic & Housing Research group, do not necessarily represent the views of Freddie Mac or its management, should not be construed as indicating Freddie Mac's business prospects or expected results, and are subject to change without notice. Natural Language Processing: Building sequence models Housing Price Prediction size. In Boston 0. The Australian Financial Review reports the latest news from business, finance, investment and politics, updated in real time. Prediction interval: predict(lm(log(price) ~ sqft), newdata = data. It shows the variables in the dataset and its interdependencies. The results are shown in Figure 6. PropertyShark is a real estate data provider of in-depth information on any US property, commercial or residential. MBTA - Massachusetts Bay Transportation Authority. While some code has already been implemented to get you started, you will need to implement additional functionality when requested to. Unable to find location, please try again. housing market is now cooling. A Price Prediction Method In Real Estate Market by Heng Li B. Statistical Analysis and Data Exploration¶. Quicken Loans received the highest score in the J. Another way to make the models more interpretable is to replace the black box with a simpler model - a decision tree. Look for price appreciation to slow down. Page 1 of 56 Housing Price Prediction Using Support Vector Regression A Project Report Presented to The Department of Computer Science San Jose State University. First machine learning project — Boston House Price Prediction After having gone through some online ML courses, I realised I was still clueless as to how to start and complete a machine learning…. His trial began this week. In either case, the travel time to Earth for such material leaving the sun is 1 to 3 days. Weather Forecast. Morehouse News Spike Lee Honored With Awards. Connecting Our Real Estate Community. This week we look forward to convening an Opioid Task Force meeting to address the important roles pharmacists play in combating the opioid crisis, a multifaceted issue that requires sustained efforts by all members of the interprofessional care team. After completing this step-by-step tutorial, you will know: How to load a CSV. Get the stats and stay informed. boston boats - craigslist CL boston boston albany, NY cape cod catskills central NJ eastern CT glens falls hartford hudson valley jersey shore long island maine new hampshire new haven new york north jersey northwest CT oneonta plattsburgh poconos rhode island south coast utica vermont western mass worcester >. This repository contains files for Udacity's Machine Learning Nanodegree Project: Boston House Price Prediction udacity-nanodegree data-analysis-udacity boston-housing-price-prediction Updated Aug 31, 2019. ML | Boston Housing Kaggle Challenge with Linear Regression Boston Housing Data: This dataset was taken from the StatLib library and is maintained by Carnegie Mellon University. How It Affects You. The central tendency for the given dataset with respect to the mean and the median are as follows: mean price of house: 22. 000000$ (-100. Download Open Datasets on 1000s of Projects + Share Projects on One Platform. Microsoft is radically simplifying cloud dev and ops in first-of-its-kind Azure Preview portal at portal. 500k from high frequency trading from 2009 to 2010. Vehicle Movement Based Street Lights Project mainly aims at saving energy. Follow the stock market today on TheStreet. 1 Predicting Boston Housing Prices. This section is an exploratory analysis of the Boston Housing data which will introduce the data and some changes that I made, summarize the median-value data, then look at the features to make an initial hypothesis about the value of the client's home. View daily MI weather updates, watch videos and photos, join the discussion in forums. Code for the housing demo shown in this post in GitHub and AI Hub. Of the low crime towns, there is a lot of variation in housing prices. 2 This means that our current prediction for the given house is credible. 4% or approximately $41 per month, according to a Defense Department news release. How zoning helps keep the Boston-area housing market pricey and tight. Dictionary-like object, the interesting attributes are: ‘data’, the data to learn, ‘target’, the regression targets, ‘DESCR’, the full description of the dataset, and ‘filename’, the physical location of boston csv dataset (added in version 0. Learn more about Rift, Rift S, Quest and Go. The central tendency for the given dataset with respect to the mean and the median are as follows: mean price of house: 22. Check in online on KLM. The fact-checkers, whose work is more and more important for those who prefer facts over lies, police the line between fact and falsehood on a day-to-day basis, and do a great job. Today, my small contribution is to pass along a very good overview that reflects on one of Trump’s favorite overarching falsehoods. Namely: Trump describes an America in which everything was going down the tubes under  Obama, which is why we needed Trump to make America great again. And he claims that this project has come to fruition, with America setting records for prosperity under his leadership and guidance. “Obama bad; Trump good” is pretty much his analysis in all areas and measurement of U.S. activity, especially economically. Even if this were true, it would reflect poorly on Trump’s character, but it has the added problem of being false, a big lie made up of many small ones. Personally, I don’t assume that all economic measurements directly reflect the leadership of whoever occupies the Oval Office, nor am I smart enough to figure out what causes what in the economy. But the idea that presidents get the credit or the blame for the economy during their tenure is a political fact of life. Trump, in his adorable, immodest mendacity, not only claims credit for everything good that happens in the economy, but tells people, literally and specifically, that they have to vote for him even if they hate him, because without his guidance, their 401(k) accounts “will go down the tubes.” That would be offensive even if it were true, but it is utterly false. The stock market has been on a 10-year run of steady gains that began in 2009, the year Barack Obama was inaugurated. But why would anyone care about that? It’s only an unarguable, stubborn fact. Still, speaking of facts, there are so many measurements and indicators of how the economy is doing, that those not committed to an honest investigation can find evidence for whatever they want to believe. Trump and his most committed followers want to believe that everything was terrible under Barack Obama and great under Trump. That’s baloney. Anyone who believes that believes something false. And a series of charts and graphs published Monday in the Washington Post and explained by Economics Correspondent Heather Long provides the data that tells the tale. The details are complicated. Click through to the link above and you’ll learn much. But the overview is pretty simply this: The U.S. economy had a major meltdown in the last year of the George W. Bush presidency. Again, I’m not smart enough to know how much of this was Bush’s “fault.” But he had been in office for six years when the trouble started. So, if it’s ever reasonable to hold a president accountable for the performance of the economy, the timeline is bad for Bush. GDP growth went negative. Job growth fell sharply and then went negative. Median household income shrank. The Dow Jones Industrial Average dropped by more than 5,000 points! U.S. manufacturing output plunged, as did average home values, as did average hourly wages, as did measures of consumer confidence and most other indicators of economic health. (Backup for that is contained in the Post piece I linked to above.) Barack Obama inherited that mess of falling numbers, which continued during his first year in office, 2009, as he put in place policies designed to turn it around. By 2010, Obama’s second year, pretty much all of the negative numbers had turned positive. By the time Obama was up for reelection in 2012, all of them were headed in the right direction, which is certainly among the reasons voters gave him a second term by a solid (not landslide) margin. Basically, all of those good numbers continued throughout the second Obama term. The U.S. GDP, probably the single best measure of how the economy is doing, grew by 2.9 percent in 2015, which was Obama’s seventh year in office and was the best GDP growth number since before the crash of the late Bush years. GDP growth slowed to 1.6 percent in 2016, which may have been among the indicators that supported Trump’s campaign-year argument that everything was going to hell and only he could fix it. During the first year of Trump, GDP growth grew to 2.4 percent, which is decent but not great and anyway, a reasonable person would acknowledge that — to the degree that economic performance is to the credit or blame of the president — the performance in the first year of a new president is a mixture of the old and new policies. In Trump’s second year, 2018, the GDP grew 2.9 percent, equaling Obama’s best year, and so far in 2019, the growth rate has fallen to 2.1 percent, a mediocre number and a decline for which Trump presumably accepts no responsibility and blames either Nancy Pelosi, Ilhan Omar or, if he can swing it, Barack Obama. I suppose it’s natural for a president to want to take credit for everything good that happens on his (or someday her) watch, but not the blame for anything bad. Trump is more blatant about this than most. If we judge by his bad but remarkably steady approval ratings (today, according to the average maintained by 538.com, it’s 41.9 approval/ 53.7 disapproval) the pretty-good economy is not winning him new supporters, nor is his constant exaggeration of his accomplishments costing him many old ones). I already offered it above, but the full Washington Post workup of these numbers, and commentary/explanation by economics correspondent Heather Long, are here. On a related matter, if you care about what used to be called fiscal conservatism, which is the belief that federal debt and deficit matter, here’s a New York Times analysis, based on Congressional Budget Office data, suggesting that the annual budget deficit (that’s the amount the government borrows every year reflecting that amount by which federal spending exceeds revenues) which fell steadily during the Obama years, from a peak of $1.4 trillion at the beginning of the Obama administration, to $585 billion in 2016 (Obama’s last year in office), will be back up to $960 billion this fiscal year, and back over $1 trillion in 2020. (Here’s the New York Times piece detailing those numbers.) Trump is currently floating various tax cuts for the rich and the poor that will presumably worsen those projections, if passed. As the Times piece reported: