MATH FOR AI

BEST APPROACH TO MACHINE LEARNING /DEEP LEARNING ?

WHAT RESOURCES AND APPROACH ONE SHOULD FOLLOW WHILE LEARNING DEEP LEARNING OR MACHINE LEARNING?

MATHEMATICS FOR MACHINE LEARNING

STUDENTS FOLLOW VARIOUS APPROACHES WHEN THEY WANT TO LEARN A NEW SKILL. WHEN IT COMES TO SKILLS LIKE “DATA SCIENCE” , THE STUDENTS ARE GENERALLY CONFUSED ABOUT THE APPROACH. THE COMMON QUESTIONS RELATED TO MACHINE LEARNING AND DEEP LEARNING ARE:

  1. HOW MUCH MATH IS REQUIRED? SHOULD I BOTHER TO STUDY BOOKS ON MACHINE LEARNING OR IS ONLINE MATERIAL ENOUGH?
  2. IS PYTHON BEST FOR DATA SCIENCE? WHY IS THAT MAJOR RESOURCES HAVE THEIR TUTORIALS IN PYTHON
  3. BEST ONLINE MATERIAL/COURSES?
  4. WHAT AND HOW MANY PROJECTS SHOULD I DO?

LETS ANSWER ALL THESE QUESTIONS ONE BY ONE

THE MATH REQUIRED

TO ANSWER THIS QUESTION SIMPLY CONSIDER THE DIFFERENCE BETWEEN A MEDICINE SHOP OWNER AND A DOCTOR . THE MEDICINE SHOP OWNER CAN PROVIDE YOU A MEDICINE FOR ANY PARTICULAR DISEASE , WITH EXPERIENCE HE HAS THE NAMES OF ALMOST ALL THE MEDICINES HE HAS IN HIS STORE. BUT SEPARATES A DOCTOR FROM HIM IS THE FACT THAT A DOCTOR CAN INVENT A NEW MEDICINE FORMULA . SIMILARLY JUST MAKING MODELS WITHOUT VISUALISING / UNDERSTANDING THE MATH BEHIND IT WILL MAKE YOU AN EXPERT ONLY WHEN YOU FACE PROBLEMS THAT ARE COMMON . THE MOMENT YOU SEE A NEW CHALLENGING DATA SET , YOU ARE SURE TO GET CONFUSED . THE BASIC MATHEMATICS KNOWLEDGE THAT ONE REQUIRES CAN BE FOUND HERE .

IS PYTHON BEST FOR DATA SCIENCE

PYTHON IS ONE OF THE MOST TRENDING LANGUAGES IN THE INDUSTRY RIGHT NOW . BE IT YOUTUBE OR ONLINE COURSES ,NOWADAYS ALMOST EVERYWHERE THE TUTORIALS ON DATA SCIENCES , MACHINE LEARNING , NEURAL NETWORKS CAN BE SEEN IN PYTHON . THE PANDAS,NUMPY,SCIKITLEARN MODULES PRESENT IN PYTHON HAVE EXCELLENT FEATURES THAT MAKES DATA ANALYSIS EASIER AND YOU CAN FOCUS MORE ON FEATURE ENGINEERING ,MODEL MATHEMATICS RATHER THAN CODING SYNTAX.

BEST ONLINE MATERIAL/COURSES

DIFFERENT CHANNELS /PLATFORMS HAVE DIFFERENT APPROACHES TO TEACH A DISCIPLINE .HERE IS AN APPROACH WHICH I FOUND BEST WHILE LEARNING ML/ DL :

  1. CHOOSE ONE SOURCE WHICH CLEARS YOUR BASICS, HELPS YOU GRASP THE CORE MATHEMATICS IN A MORE ACADEMIC APPROACH . NPTEL IS THE BEST PLATFORM FOR THIS ONE
  2. CHOOSE ONE SOURCE WHICH EXPLAINS IN A DYNAMIC WAY AN OVERVIEW OF THE MATHEMATICS ,EXAMPLE : A YOUTUBE CHANNEL OF YOUR CHOICE .
  3. ONE PROJECT ORIENTED SOURCE.

SUCH AN APPROACH WILL HELP YOU LEARN ALL DOMAINS OF THE SKILL.

WHAT PROJECTS SHOULD I DO

BEING A BEGINNER ONE SHOULD NOT RESTRICT HERSELF/HIMSELF TO ONLY CERTAIN TOPICS . MOREOVER THE INITIAL PROJECTS YOU MAKE AS A STUDENT ARE NOT FOR CREATING NEW INVENTIONS ,RATHER ITS FOR HAVING A HANDS ON EXPERIENCE OF GOING TROUGH THE STEPS ONE GOES THROUGH WHILE MAKING A MODEL . AND A BEGINNER IS EXPECTED TO HAVE KNOWLEDGE IN ALL BASIC DOMAINS . ITS BETTER TO HAVE SUFFICIENTLY GOOD LENGTH PROJECTS ON 5 TOPICS ,RATHER THAN HAVING A HUGE ONE CENTERED AROUND A SINGLE TOPIC . EXPLORATION IS THE KEY .

HERE IS THE LINK TO THE DEEP LEARNING SERIES ON NPTEL . ITS FREE AND IS ONE OF THE BEST SOURCES ON INTERNET WHEN IT COMES TO UNDERSTANDING DEEP LEARNING .

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