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Data Science Demo 1
In this Demo you will understand what is data science,who is data scientist ...etc
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About Faculty 04 minLecture1.1
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What is Data Science 11 minLecture1.2
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Who is data scientist 06 minLecture1.3
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who can learn this course 11 minLecture1.4
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Data Science Process Quick Tour 27 minLecture1.5
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Data Science Quiz 4 questionsQuiz1.1
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Python Introduction and Anaconda Installation 2
We will learn what is python and why we are using python in data science . why not other languages like c,c++,jave ... etc. We also learn how to install anaconda and more information about spyder IDE
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Python Introduction and Anaconda Installation 47 minLecture2.1
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Quiz on Introduction 6 questionsQuiz2.1
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Quiz on Installation 4 questionsQuiz2.2
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Python Data Types 7
We will learn int,float,complex,bool,str data types
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Python as Calculator 10 minLecture3.1
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Quiz on playing numbers 2 questionsQuiz3.1
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Python int,float and complex data types 09 minLecture3.2
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Quiz on numbers data types 4 questionsQuiz3.2
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Python string Data types 24 minLecture3.3
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Quiz on Strings 7 questionsQuiz3.3
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Mutable Vs Immutable 16 minLecture3.4
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Python Lists 5
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Define List 14 minLecture4.1
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Read List Items 10 minLecture4.2
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Change List Items 08 minLecture4.3
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List Memory allocation 05 minLecture4.4
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Quiz on List 2 questionsQuiz4.1
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Operators 4
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Comparison Operators 19 minLecture5.1
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Boolean Operators and Numpy Boolean Operators 11 minLecture5.2
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Filtering data frame using operators 26 minLecture5.3
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Quiz on Operators 2 questionsQuiz5.1
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Control Flows 6
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if elif elif else 16 minLecture6.1
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while loop 13 minLecture6.2
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for loop on string ,list,dict 21 minLecture6.3
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for loop on numpy array 13 minLecture6.4
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for loop on data frame 12 minLecture6.5
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Quiz on Control Flows 7 questionsQuiz6.1
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Functions 7
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System Defined Functions 12 minLecture7.1
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User Defined Functions 25 minLecture7.2
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Tuple 13 minLecture7.3
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Scope of variable objects in functions 20 minLecture7.4
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Nested Functions 15 minLecture7.5
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Default and Flexible Arguments 23 minLecture7.6
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Quiz on Functions 3 questionsQuiz7.1
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Methods 2
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Methods 25 minLecture8.1
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Quiz on Methods 0 questionQuiz8.1
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Modules 2
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Create and use Modules 26 minLecture9.1
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Quiz on Modules 0 questionQuiz9.1
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Packages 3
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User Defined Packages 46 minLecture10.1
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System Defined Packages 18 minLecture10.2
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Quiz on packages 0 questionQuiz10.1
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Dictionaries 5
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Why we need dictionaries and Create simple dictionary 12 minLecture11.1
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Dictionary Keys are Mutable and values are immutable 12 minLecture11.2
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Nested Dictionaries 07 minLecture11.3
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Create DataFrame using dictionary 12 minLecture11.4
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Quiz on Dictionaries 2 questionsQuiz11.1
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Lambda Functions 4
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Lambda Map Function 20 minLecture12.1
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Lambda Filter Function 10 minLecture12.2
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Lambda Reduce Function 09 minLecture12.3
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Quiz on Lambda Functions 2 questionsQuiz12.1
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Syntax Errors and Exceptions 4
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Syntax Errors 08 minLecture13.1
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Exceptions 08 minLecture13.2
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User Defined Exceptions 10 minLecture13.3
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Quiz on erros 0 questionQuiz13.1
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Iterables and Iterators 4
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Iterables and Iterators 16 minLecture14.1
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Use iterators as function arguments 12 minLecture14.2
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Zip and unzip 07 minLecture14.3
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Quiz on iterables 0 questionQuiz14.1
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List Comprehension 4
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List Comprehension to avoid loop or lambda functions 11 minLecture15.1
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List Comprehension to avoid nested loops 06 minLecture15.2
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List Comprehension with conditions 04 minLecture15.3
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Quiz on List Comprehension 0 questionQuiz15.1
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Generators 1
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Generators 17 minLecture16.1
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Numpy Packages 5
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Intro to Numpy 36 minLecture17.1
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About NDarray 20 minLecture17.2
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Quiz 0 questionQuiz17.1
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Numpy 2D arrays 13 minLecture17.3
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Basic Numpy stats 11 minLecture17.4
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Pandas(Python Data Analysis Library) 8
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Pandas Intro and Slicing DataFrame 23 minLecture18.1
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DataFrame Filters 36 minLecture18.2
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Transformations on DataFrame 13 minLecture18.3
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Advanced Indexing 22 minLecture18.4
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Create Index at the time of file import 06 minLecture18.5
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Hierarchical indexing 18 minLecture18.6
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Stack and Unstack 15 minLecture18.7
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Groupby and aggregations 12 minLecture18.8
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Matplotlib Visulization 5
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Intro to Matplotlib Visulization 32 minLecture19.1
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Multiple plots on single axis 12 minLecture19.2
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Different line plots on distinct axes using axes 09 minLecture19.3
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Different line plots on distinct axes using subplot 14 minLecture19.4
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Legend Annotation and Styles 21 minLecture19.5
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Importing Data from Files 7
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About Working Directory 14 minLecture20.1
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Importing Data from FlatFiles 09 minLecture20.2
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Importing Data using loadtxt and genfromtxt 37 minLecture20.3
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Working With Excel Reading 17 minLecture20.4
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Working With Excel writing 08 minLecture20.5
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Working with SAS and STATA files 11 minLecture20.6
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Working with HDF5 Files 15 minLecture20.7
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Importing Data From RDBMS 2
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Working with SQLite Database Part 1 16 minLecture21.1
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Working with SQLite Database Part 2 18 minLecture21.2
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Import from internet 7
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Import web Data 12 minLecture22.1
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Import using URLlib packages 08 minLecture22.2
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Import using requests package 14 minLecture22.3
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Working with JSON files 12 minLecture22.4
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Working with Movie Database 14 minLecture22.5
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Working with Wikipedia database 02 minLecture22.6
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Working with Twitter 10 minLecture22.7
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Machine Learning Pre Processing 10
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Data Cleaning Introduction 09 minLecture23.1
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Melt or unpivot 14 minLecture23.2
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Pivot and Pivot Table 08 minLecture23.3
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Using Concat function to merge data frames row wise or column wise 14 minLecture23.4
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Merge or Joins 14 minLecture23.5
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Data Type Conversions 12 minLecture23.6
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Regular Expressions 12 minLecture23.7
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Dropping Duplicate Records 05 minLecture23.8
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Filling Missing Data 08 minLecture23.9
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Asserts 09 minLecture23.10
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Machine Learning Models or Algorithms 28
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Machine Learning Introduction 16 minLecture24.1
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Types of Machine Learning Algorithm 37 minLecture24.2
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k Nearest Neighbor Algorithm 14 minLecture24.3
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K Nearest Neighbor Algorithm Non Parametric Method 19 minLecture24.4
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Understand IRIS dataset 14 minLecture24.5
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KNN lab1 24 minLecture24.6
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KNN Train and Test (need to take one more time) 10 minLecture24.7
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KNN Hyper Parameter Tunning 37 minLecture24.8
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Logistic Regression Intro 13 minLecture24.9
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Logistic Regression Lab1 20 minLecture24.10
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Confusion Matrix ,Cllasification Report ,ROC curve and AUC 30 minLecture24.11
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Hyper Parameter Tuning 12 minLecture24.12
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Linear regression Algorithm Introduction 13 minLecture24.13
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Linear Regression Algorithm Lab 1 22 minLecture24.14
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Microsoft Azure ML cloud Introduction 1 24 minLecture24.15
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Microsoft Azure ML cloud Introduction 2 31 minLecture24.16
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R2 Square and RMSE Calculation 20 minLecture24.17
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Train and Test Split Linear Regression 10 minLecture24.18
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Cross Validation or k fold 08 minLecture24.19
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Linear regression One more example using Boston Data 04 minLecture24.20
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Support vector machines (SVMs) 31 minLecture24.21
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ML Pre Processing ## Outliers 13 minLecture24.22
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ML Pre Processing ## Categorical Data 20 minLecture24.23
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ML Pre Processing ## Missing Data Data 18 minLecture24.24
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ML Pre Processing ## ML Pipeline 20 minLecture24.25
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Unsupervised Learning Introduction 14 minLecture24.26
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Unsupervised Learning # K Means Clustering 38 minLecture24.27
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Unsupervised Learning # Clustering Quality 14 minLecture24.28
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NLU / NLP / Text Analytics/ Text Mining 11
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NLP # Introduction 20 minLecture25.1
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NLP # Regular Expressions# Tokenization 26 minLecture25.2
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NLP # Word # Sentences # tweet #regex Tokenizations 24 minLecture25.3
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123.Word counts with bag of words 12 minLecture25.4
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124.Text pre-processing 09 minLecture25.5
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125. Lemmatization_or_Stemming 10 minLecture25.6
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126. Gensim 08 minLecture25.7
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127. Tf-idf with gensim 05 minLecture25.8
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128. Named Entity Recognition(NER) 29 minLecture25.9
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129. SpaCy_Displacy 28 minLecture25.10
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130. Multilingual NER with polyglot 05 minLecture25.11
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131. Building a fake news classifier 40 minLecture25.12
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Data Science Project Using NLP 8
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132. NLP ChatBot Project Introduction 19 minLecture26.1
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133. Understanding intents and entities 29 minLecture26.2
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134. Word Vectors 18 minLecture26.3
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135.RASA NLU Intro 45 minLecture26.4
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136. Using RASA NLU to identify Entities 18 minLecture26.5
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137. Access Data from SQLite Database with parameters 30 minLecture26.6
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138. Exploring a DB with natural language 12 minLecture26.7
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139. Creating SQL from natural language 21 minLecture26.8
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Exams 1
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Level 1 Exam 3 questionsQuiz27.1
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Deep Learning 12
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05_of_08_Deep_Learning_or_Neural_Network/ 30 minLecture28.1
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DSP_L5_01_Introduction 30 minLecture28.2
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DSP_L5_01_Introduction 30 minLecture28.3
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DSP_L5_02_Model_Optimization 30 minLecture28.4
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DSP_L5_03_Gradient_Descent 30 minLecture28.5
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DSP_L5_03_Gradient_DescentLecture28.6
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DSP_L5_04_Backward_Propagation 30 minLecture28.7
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DSP_L5_04_Backward_Propagation 30 minLecture28.8
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A Step by Step Backpropagation Example – Matt Mazur 30 minLecture28.9
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DSP_L5_05_Keras_Introduction 30 minLecture28.10
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DSP_L5_05_Keras_Regression_Model 30 minLecture28.11
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DSP_L5_05_Keras_Regression_Model 30 minLecture28.12
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DSP_L5_06_Creating_Keras_Classification_Models 30 minLecture28.13
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DSP_L5_07_Understanding_Model_Optimization 30 minLecture28.14
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DSP_L5_08_Model_Validation 30 minLecture28.15
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DSP_L5_08_Model_Validation 30 minLecture28.16
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DSP_L5_08_Model_Validation 30 minLecture28.17
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DSP_L5_09_Model_CapacityLecture28.18
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Create a New Repository 30 minLecture28.19
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Project1_Identify_hand_written_digits 30 minLecture28.20
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Project1_Identify_hand_written_digits 30 minLecture28.21
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Project1_Identify_hand_written_digits 30 minLecture28.22
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