Take a data-first and use-case driven approach to understanding machine learning and deep learning concepts with Low-Code AI. This hands-on guide presents three problem-focused ways to learn ML: no code using AutoML, low-code using BigQuery ML, and custom code using scikit-learn and Keras. You'll learn key ML concepts by using real-world datasets with realistic problems. Business and data analysts get a project-based introduction to ML/AI using a detailed, data-driven approach: loading and analyzing data, feeding data into an ML model; building, training, and testing; and deploying the model into production. Authors Michael Abel and Gwendolyn Stripling show you how to build machine learning models for retail, healthcare, financial services, energy, and telecommunications. You'll learn how to: Distinguish structured and unstructured data and understand the different challenges they present Visualize and analyze data Preprocess data for input into a machine learning model Differentiate between the regression and classification supervised learning models Compare different machine learning model types and architectures, from no code to low-code to custom training Design, implement, and tune ML models Export data to a GitHub repository for data management and governance

Now available in paperback, William C. Banfield's acclaimed collection of interviews delves into the lives and work of forty-one Black composers. Each of the profiled artists offers a candid self-portrait that explores areas from training and compositional techniques to working in a exclusive canon that has existed for a very long time. At the same time, Banfield draws on sociology, Western concepts of art and taste, and vernacular musical forms like blues and jazz to provide a frame for the artists' achievements and help to illuminate the ongoing progress and struggles against industry barriers. Expanded illustrations and a new preface by the author provide invaluable added context, making this new edition an essential companion for anyone interested in Black composers or contemporary classical music. Composers featured: Michael Abels, H. Leslie Adams, Lettie Beckon Alston, Thomas J. Anderson, Dwight Andrews, Regina Harris Baiocchi, David Baker, William C. Banfield, Ysaye Maria Barnwell, Billy Childs, Noel DaCosta, Anthony Davis, George Duke, Leslie Dunner, Donal Fox, Adolphus Hailstork, Jester Hairston, Herbie Hancock, Jonathan Holland, Anthony Kelley, Wendell Logan, Bobby McFerrin, Dorothy Rudd Moore, Jeffrey Mumford, Gary Powell Nash, Stephen Newby, Coleridge-Taylor Perkinson, Michael Powell, Patrice Rushen, George Russell, Kevin Scott, Evelyn Simpson-Curenton, Hale Smith, Billy Taylor, Frederick C. Tillis, George Walker, James Kimo Williams, Julius Williams, Tony Williams, Olly Wilson, and Michael Woods

Leasinggeschafte sind schwebende Geschiifte; Anspruche und Leistungsverpflichtungen sowie kiinftige Erfolge werden nach herrschender Meinung nicht bilanziert. Die aus der externen Rechnungslegung verfugbaren Inforrnationen sind daher unvollstandig. Aufgrund des leasingtypisch degressiven Kostenverlaufs bewirkt wachsendes Neugeschaft eine Gewinnverlagerung in die Zukunft, d.h. bei vertragsgemaBem Ablauf eine Erhohung des noch nicht realisierten Erfolgspotentials zu Lasten der Gewinnausweise abgelaufener Peri oden. Rticklaufigem Neugeschaft folgen umgekehrt Auflosungen von in der Vergangenheit begrundeten Erfolgspotentialen und steigende Gewinnausweise. Zugleich fuhrt die Substitu tion von Fremdkapital durch das aus der Aufwandsvorverrechnung verfugbare intern Mittel aufkommen zu einer Bilanzverkiirzung. Ausgewiesenes Kapital und tatsachlicher Kapitalein satz weichen urn internes Mittelaufkommen voneinander ab, was jedoch aus dem externen Rechnungswesen nicht erkennbar ist. Der Verfasser der vorliegenden Arbeit war tiber lange Jahre in leitender Stellung im Rech nungswesen einer groBen deutschen Mobilien-Leasinggesellschaft tatig. Er will in Kenntnis der beschriebenen Mangel des Rechnungswesens einer Leasinggesellschaft ein Controllingsy stem entwickeln, das realisiertes und schwebendes Leasinggeschaft vollstandig fur den ge samten Abwicklungszeitraum des Leasingbestandes darstellt. Es wird verdeutlicht, wie sich die Geschaftsentwicklung auf Kapitaleinsatz, Liquiditat, Rentabilitat und Gewinn einer Lea singgesellschaft im Abwicklungszeitraum auswirkt, urn so eine Entscheidungsgrundlage fur die strategische Planung des Wachstums einer Leasinggesellschaft bereitzustellen."

Now available in paperback, William C. Banfield’s acclaimed collection of interviews delves into the lives and work of forty-one Black composers. Each of the profiled artists offers a candid self-portrait that explores areas from training and compositional techniques to working in a exclusive canon that has existed for a very long time. At the same time, Banfield draws on sociology, Western concepts of art and taste, and vernacular musical forms like blues and jazz to provide a frame for the artists’ achievements and help to illuminate the ongoing progress and struggles against industry barriers. Expanded illustrations and a new preface by the author provide invaluable added context, making this new edition an essential companion for anyone interested in Black composers or contemporary classical music. Composers featured: Michael Abels, H. Leslie Adams, Lettie Beckon Alston, Thomas J. Anderson, Dwight Andrews, Regina Harris Baiocchi, David Baker, William C. Banfield, Ysaye Maria Barnwell, Billy Childs, Noel DaCosta, Anthony Davis, George Duke, Leslie Dunner, Donal Fox, Adolphus Hailstork, Jester Hairston, Herbie Hancock, Jonathan Holland, Anthony Kelley, Wendell Logan, Bobby McFerrin, Dorothy Rudd Moore, Jeffrey Mumford, Gary Powell Nash, Stephen Newby, Coleridge-Taylor Perkinson, Michael Powell, Patrice Rushen, George Russell, Kevin Scott, Evelyn Simpson-Curenton, Hale Smith, Billy Taylor, Frederick C. Tillis, George Walker, James Kimo Williams, Julius Williams, Tony Williams, Olly Wilson, and Michael Woods