BEGIN:VCALENDAR
VERSION:2.0
PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:Asia/Calcutta
BEGIN:STANDARD
DTSTART:19451014T230000
TZOFFSETFROM:+0630
TZOFFSETTO:+0530
TZNAME:IST
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END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20200630T175901Z
UID:0FDE2990-F883-420E-BA6D-8058B6B97F54
DTSTART;TZID=Asia/Calcutta:20200630T140000
DTEND;TZID=Asia/Calcutta:20200630T160000
DESCRIPTION:- Mr. Anudeep started by giving the students a recap of what wa
 s already discussed in the previous classes and continued his class by int
 roducing us to regression.\n- He told us what regression was and the diffe
 rent ways it can be used.\n- He went on to explain the concept of Simple R
 egression and how to calculate it and the mathematics behind it.\n- He exp
 lained the concept of Residual Error and Squared Error and how to calculat
 e it.\n- He then explained the concept of Multiple Regression and when it
 ’s used.\n- He helped us understand the importance of using the correct 
 models for a given set of data.\n- He told us what Gradient Descent is and
  how to use it to minimize error in a model.\n- He explained how to use po
 lynomial regression for Non-Linear data and the concept of Logistic Regres
 sion.\n- He explained the definition of terms like Precision\, Recall\, an
 d Accuracy\, and how to calculate them.\n- He explained the different cate
 gories of Logistic Regression like Binomial\, Multinomial\, and Ordinal an
 d how to access Performance.\n- He explained the concepts of Feature Selec
 tion and Lasso Regression.\n- In the end\, he showed us some of the progra
 ms that he had and then opened the lecture to questions.\n\nSpeaker(s): Mr
 . Peddi Anudeep\, \n\nAgenda: \nThe goal of the lecture was to introduce t
 he concept of Regression and help the students understand it’s importanc
 e in the field of Machine Learning.\n\nHyderabad\, Andhra Pradesh\, India
LOCATION:Hyderabad\, Andhra Pradesh\, India
ORGANIZER:tharunkumar@ieee.org
SEQUENCE:0
SUMMARY:Lecture on "Regression"
URL;VALUE=URI:https://events.vtools.ieee.org/m/234421
X-ALT-DESC:Description: <br /><ul>\n<li style="font-weight: 400\;"><span st
 yle="font-weight: 400\;">Mr. Anudeep started by giving the students a reca
 p of what was already discussed in the previous classes and continued his 
 class by introducing us to regression.</span></li>\n<li style="font-weight
 : 400\;"><span style="font-weight: 400\;">He told us what regression was a
 nd the different ways it can be used.</span></li>\n<li style="font-weight:
  400\;"><span style="font-weight: 400\;">He went on to explain the concept
  of Simple Regression and how to calculate it and the mathematics behind i
 t.</span></li>\n<li style="font-weight: 400\;"><span style="font-weight: 4
 00\;">He explained the concept of Residual Error and Squared Error and how
  to calculate it.</span></li>\n<li style="font-weight: 400\;"><span style=
 "font-weight: 400\;">He then explained the concept of Multiple Regression 
 and when it&rsquo\;s used.</span></li>\n<li style="font-weight: 400\;"><sp
 an style="font-weight: 400\;">He helped us understand the importance of us
 ing the correct models for a given set of data.</span></li>\n<li style="fo
 nt-weight: 400\;"><span style="font-weight: 400\;">He told us what Gradien
 t Descent is and how to use it to minimize error in a model.</span></li>\n
 <li style="font-weight: 400\;"><span style="font-weight: 400\;">He explain
 ed how to use polynomial regression for Non-Linear data and the concept of
  Logistic Regression.</span></li>\n<li style="font-weight: 400\;"><span st
 yle="font-weight: 400\;">He explained the definition of terms like Precisi
 on\, Recall\, and Accuracy\, and how to calculate them.</span></li>\n<li s
 tyle="font-weight: 400\;"><span style="font-weight: 400\;">He explained th
 e different categories of Logistic Regression like Binomial\, Multinomial\
 , and Ordinal and how to access Performance.</span></li>\n<li style="font-
 weight: 400\;"><span style="font-weight: 400\;">He explained the concepts 
 of Feature Selection and Lasso Regression.</span></li>\n<li style="font-we
 ight: 400\;"><span style="font-weight: 400\;">In the end\, he showed us so
 me of the programs that he had and then opened the lecture to questions.</
 span></li>\n</ul><br /><br />Agenda: <br /><p><span style="font-weight: 40
 0\;">The goal of the lecture was to introduce the concept of Regression an
 d help the students understand it&rsquo\;s importance in the field of Mach
 ine Learning.</span></p>
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