E-Book on Basic Guide to Data Science (for non-tech students)
This book is truly based on basics of Data Science, where you will an overall idea of it through various topics related to Data Science. It is designed for students coming from Non-Tech backgrounds. Read thoroughly to get the most out of it.
Chapter 1 : ABOUT DATA SCIENCE
Chapter 2 : BIG DATA ANALYTICS
Chapter 3 : DATA ENGEERING
Chapter 4 : NATURAL LANGUAGE PROCESSING
Chapter 5 : DEEP LEARNING
Chapter 6 : TIME SERIES ANALYSIS
Chapter 7 : IMAGE PROCESSING AND COMPUTER VISION
Chapter 8 : DATA WAREHOUSING
Chapter 9 : CLOUD COMPUTING FOR DATA SCIENCE
Chapter 10 : DATA ETHICS AND PRIVACY
Chapter 11 : DATA GOVERNANCE
Chapter 12 : DATA MINING
Chapter 13 : DATA STORYTELLING
Chapter 14 : DIMENSIONALITY REDUCTION TECHNIQUES
Chapter 15 : ENSEMBLE LEARNING
Chapter 16 : HYPERPARAMETER TUNING
Chapter 17 : NEURAL NETWORKS
Chapter 18 : RECOMMENDER SYSTEM
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It includes in depth information about the Data Science but the information is in the most simplest way possible, which is specially designed for students from Non-CS backgrounds like BA/BCom/BBA/BSc or any other field other than computer science.
&caption=undefined&description=<p>This book is truly based on basics of Data Science, where you will an overall idea of it through various topics related to Data Science. It is designed for students coming from Non-Tech backgrounds. Read thoroughly to get the most out of it.</p><p><br></p><p><strong>Chapter 1 :</strong> ABOUT DATA SCIENCE </p><p><strong>Chapter 2 :</strong> BIG DATA ANALYTICS </p><p><strong>Chapter 3 :</strong> DATA ENGEERING</p><p><strong>Chapter 4 :</strong> NATURAL LANGUAGE PROCESSING </p><p><strong>Chapter 5 :</strong> DEEP LEARNING </p><p><strong>Chapter 6 :</strong> TIME SERIES ANALYSIS </p><p><strong>Chapter 7 : </strong>IMAGE PROCESSING AND COMPUTER VISION</p><p><strong>Chapter 8 :</strong> DATA WAREHOUSING</p><p><strong>Chapter 9 : </strong>CLOUD COMPUTING FOR DATA SCIENCE</p><p><strong>Chapter 10 : </strong>DATA ETHICS AND PRIVACY</p><p><strong>Chapter 11 :</strong> DATA GOVERNANCE </p><p><strong>Chapter 12 : </strong>DATA MINING</p><p><strong>Chapter 13 : </strong>DATA STORYTELLING </p><p><strong>Chapter 14 :</strong> DIMENSIONALITY REDUCTION TECHNIQUES</p><p><strong>Chapter 15 :</strong> ENSEMBLE LEARNING </p><p><strong>Chapter 16 : </strong>HYPERPARAMETER TUNING </p><p><strong>Chapter 17 : </strong>NEURAL NETWORKS</p><p><strong>Chapter 18 :</strong> RECOMMENDER SYSTEM</p><p>-------------------------------------------------------------------------------------------------------</p><p>It includes in depth information about the<em> Data Science</em> but the information is in the most simplest way possible, which is specially designed for students from Non-CS backgrounds like BA/BCom/BBA/BSc or any other field other than computer science.</p>&redirect_uri=http://www.facebook.com){kind=link}
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