MKTG6011W Strategic Marketing Action Learning Project TESLA MOTORS Students: Marcus Chau (1155038866) Subrato Chowdhury (1155058345) Rodrigo Gonzalez (1155065430) Michael Ngan (1155040726) Carolina Quiroz (1155065428) Marcelo Seguel (1155065429) Samir Sepúlveda (1155065427) Professor: Larry K. Y. Poon Teaching Assistant: Yvonne Ning Date: May 10th‚ 2015 Index Executive Summary 1 Methodology 2 Business Strategy of Tesla in the US: 3 Value proposition and Competitive advantage:
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min_support end return ∪k Lk; increment the count of all candidates in Ck+1 that are contained in t The Apriori Algorithm: Example TID T100 T100 T100 T100 T100 T100 T100 T100 T100 List of Items I1‚ I2‚ I5 I2‚ I4 I2‚ I3 I1‚ I2‚ I4 I1‚ I3 I2‚ I3 I1‚ I3 I1‚ I2 ‚I3‚ I5 I1‚ I2‚ I3 • • • • • Consider a database‚ D ‚ consisting of 9 transactions. Suppose min. support count required is 2 (i.e. min_sup = 2/9 = 22 % ) Let minimum confidence required is 70%. We have to first find out the frequent
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Intel Core i3 Vs. i5 Vs. i7 Intel has now launched its 22 nm third generation core i3‚ i5 and i7 lineup‚ based on tri-gate (3D) transistors‚ built to make your personal computers faster and more energy efficient. Through the Intel core i3 vs. i5 vs. i7 comparison presented here‚ we compare the entirety of three generations of processors‚ to help you make a precise choice according to your computing requirements. pushing the limits of semiconductor technology‚ Intel has been constantly innovating
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processor will I go with? The Intel Core i3-4170 is a good choice processor that has some awesome perks‚ however the AMD FX- 4350 beats it in almost every aspect as a good quality processor for the price.
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50 85 % 2 0.1016 19.20 88 % 3 0.1003 19.20 89 % IO3- + 8 I- + 6 H+ → 3 I3- + 3 H2O I3- + 2 S2O32- → 3 I- + S4O62- C6H8O6 + I3- + H2O → C6H6O6 + 3 I- + 2 H+ TITRATION 1 CALCULATIONS: Initial mol of I3- 3 x (25 mL / 1000) x 0.0187 M KIO3 = 0.0014025 mol I3- Mol of I3- remaining after reaction with Ascorbic Acid (1/2) x (19.50 mL / 1000) x 0.0933 M Na2S2O3 = 9.09675 x 10-4 mol I3- remaining Mol of Ascorbic Acid = mol of I3- reacted Initial – Remaining = 4.92825 x 10-4 Mass of ascorbic acid = 4.92825
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I. Title: Kirchhoff’s Law II. Objectives: To study the application of Kirchhoff’s Law to a D.C. network by comparing the observed and the computed values of the currents in the circuit. III. Apparatus: Resistance Module‚ 1pc. Battery of two cells (3 volts)‚ 1pc. Dry cell (1.5 volts)‚ Multitester‚ 4 pairs connectors IV. Procedure with Experimental Setup: Part A. 1.) The apparatus was arranged as in diagram 1. The switches were left open until it is checked
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Evaluation of a Business Code of Ethics PHL 323 Evaluation of a Business Code of Ethics Introduction Pharmanet-i3‚ a subsidiary of inVentive Health‚ is a world leading clinical research organization committed to the advancement of health around the world. The mission of Pharmanet-i3 is to be a strategic partner to companies that develop therapeutic drugs‚ and aim to bring drugs to the public that treat disease and improve the quality of life. The company will operate within the industry’s
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conservation of charges. KCL at junction “O” I1+ I2+ I3+ I4 - I5 - I6 =0 Therefore‚ I1+ I2+ I3+ I4 = I5+I6 CIRCUIT DIAGRAM: PROCEDURE: i) Connect the circuit. As shown in circuit diagram. ii) Switch on the power supply. iii) Note the reading of ammeter OBSERVATION TABLE: Sl no. I1 (A) practically I2 (A) practically I3 (A) practically I3 (A) calculated I3 = I2+I1 CALCULATION OF CURRENT “I3” I3 = I2+I1 RESULT: Add the reading of ammeter 1(A1) & ammeter
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Contents 1. RYBCZYNSKI THEOREM ............................................................................................................................. 3 1.1 Theorem: ............................................................................................................................................. 3 1.1.1 Graphical Proof ............................................................................................................................ 3 1.1.2 Mathematical Proof .........
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Recommended Systems using Collaborative Filtering and Classification Algorithms in Data Mining Dhwani Shah 2008A7PS097G Mentor – Mrs. Shubhangi Gawali BITSC331 2011 1 BITS – Pilani‚ K.K Birla Goa INDEX S. No. 1. 2. 3. 4. 5. 6. 7. 8. 9. Topic Introduction to Recommended Systems Problem Statement Apriori Algorithm Pseudo Code Apriori algorithm Example Classification Classification Techniques k-NN algorithm Determine a good value of k References Page No. 3 5 5 7 14 16 19 24 26 2
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