Data science

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Mohamed Loey

Data Science Machine learning Big Data Data Visualization https://www.slideshare.net/mohamedloey

Education

Data Science
Google Trends
Google NGRAM
Data Science: interest by country
Data Science
Data Scientist
Data Science Roadmap
Data Science Programming Language

Data Science
0
20
40
60
80
100
120
Data Science: (Worldwide)

Data Science
0
10
20
30
40
50
60
70
80
90
100
Data Science: interest by country

Data Science
Data
Engineer
Data
Analyst
Software
Math
and
Algorithms
Computer
Science Data

Data Science
Mathematics Statistical Analysis
Machine Learning Software Engineering
Data Scientist

Data Science
Python R Julia
Java Scala C++

Data Science
Fundamentals
Statistics
Programming
Machine Learning
Text Mining / Natural Language Processing
Data Visualization
Big Data
Data Ingestion
Data Munging
Toolbox

Data Science
 Matrix
 Linear Algebra
 Binary Tree
 Hash functions
 Database basic
 Multidimensional Data model
 Relational Algebra
05%

Data Science
 Descriptive statistics
 Probability theorem
 Random variables
 Bayes theorem
 Histograms
 Continues distributions
 ANOVA
 Monte Carlo method
 Kernel density
 Regressions
 Correlations
 Euclidian distance
 Least Fit
10%

Data Science
 Variables
 Vectors
 Matrices
 Array
 List
 Functions
 Data frames
 Python/R Basics
 Manipulate Data frames
 Install Packages
15%

Data Science
 Supervised learning
 Unsupervised learning
 Training / Testing data
 Classification
 Linear Classifiers
 Decision tree
 Boosting
 Naïve Bayes classifier
30%

Data Science
 Regression
 Linear Regression
 Multiple Regression
 Ridge Regression
 Kernel Regression
 Logistic Regression
 Clustering
 Nearest Neighbor
 k-means
 Hierarchical Clustering
 Precision-Recall
30%

Data Science
 Text analysis
 Name entity recognition
 Corpus
 Market based analysis
 Feature extraction
 Using Mahout/UIMA
 Using Weka
 Using NLTK
 Classify text
40%

Data Science
 Data Exploration in R/Python
 Uni, Bi & Multivariate Viz
 ggplot2
 Histogram & Pie (Uni)
 Tree & Tree map
 Scatter plot (Bi)
 Line Charts (Bi)
50%

Data Science
 Special Charts
 Time line
 Decision Tree
 D3.js
 Tableau
 Matplotlib, vispy, bokeh, seaborn, pygal, folium, and networkx
50%

Data Science
 Map reduce Fundamentals
 Hadoop Components
 HDFS
 Data replication principles
 Name and data nodes
 Using Mahout
 Cassandra
 MongoDB
70%

Data Science
 Data formats
 Data discovery
 Data sources
 Data integration
 Data fusion
 Transformation
 Data survey
 Google OpenRefine
75%

Data Science
 Dimensionality Reduction
 Normalization
 Data scrubbing
 Handling missing values
 Denoising
 Feature Extraction
 Sampling
 Principle Component analysis
80%

Data Science
 MS Excel
 Python, R packages
 Weka, Knime, RapidMiner
 Hadoop, Spark, Storm
 D3.js, ggplot2, Shiny, Matplotlib, Tableau
 NLTK
 WebScraper
 scikit-learn, Theano, Keras
 Cassandra, Mongo DB
100%

Data Science
NumPy
SciPy
Matplotlib Pandas
Scikit Learn
Statsmodels Seaborn
Scrapy
Keras

Data Science
facebook.com/mloey
mohamedloey@gmail.com
twitter.com/mloey
linkedin.com/in/mloey
mloey@fci.bu.edu.eg

Data Science
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Data science

1. Data Science Data Science

2. Data Science Google Trends Google NGRAM Data Science: interest by country Data Science Data Scientist Data Science Roadmap Data Science Programming Language

3. Data Science 0 20 40 60 80 100 120 Data Science: (Worldwide)

4. Data Science

5. Data Science 0 10 20 30 40 50 60 70 80 90 100 Data Science: interest by country

6. Data Science Data Engineer Data Analyst Software Math and Algorithms Computer Science Data

7. Data Science Mathematics Statistical Analysis Machine Learning Software Engineering Data Scientist

8. Data Science Python R Julia Java Scala C++

9. Data Science Fundamentals Statistics Programming Machine Learning Text Mining / Natural Language Processing Data Visualization Big Data Data Ingestion Data Munging Toolbox

10. Data Science Fundamentals Statistics Programming Machine Learning Text Mining / Natural Language Processing Data Visualization Big Data Data Ingestion Data Munging Toolbox

11. Data Science  Matrix  Linear Algebra  Binary Tree  Hash functions  Database basic  Multidimensional Data model  Relational Algebra 05%

12. Data Science Fundamentals Statistics Programming Machine Learning Text Mining / Natural Language Processing Data Visualization Big Data Data Ingestion Data Munging Toolbox

13. Data Science  Descriptive statistics  Probability theorem  Random variables  Bayes theorem  Histograms  Continues distributions  ANOVA  Monte Carlo method  Kernel density  Regressions  Correlations  Euclidian distance  Least Fit 10%

14. Data Science Fundamentals Statistics Programming Machine Learning Text Mining / Natural Language Processing Data Visualization Big Data Data Ingestion Data Munging Toolbox

15. Data Science  Variables  Vectors  Matrices  Array  List  Functions  Data frames  Python/R Basics  Manipulate Data frames  Install Packages 15%

16. Data Science Fundamentals Statistics Programming Machine Learning Text Mining / Natural Language Processing Data Visualization Big Data Data Ingestion Data Munging Toolbox

17. Data Science  Supervised learning  Unsupervised learning  Training / Testing data  Classification  Linear Classifiers  Decision tree  Boosting  Naïve Bayes classifier 30%

18. Data Science  Regression  Linear Regression  Multiple Regression  Ridge Regression  Kernel Regression  Logistic Regression  Clustering  Nearest Neighbor  k-means  Hierarchical Clustering  Precision-Recall 30%

19. Data Science Fundamentals Statistics Programming Machine Learning Text Mining / Natural Language Processing Data Visualization Big Data Data Ingestion Data Munging Toolbox

20. Data Science  Text analysis  Name entity recognition  Corpus  Market based analysis  Feature extraction  Using Mahout/UIMA  Using Weka  Using NLTK  Classify text 40%

21. Data Science Fundamentals Statistics Programming Machine Learning Text Mining / Natural Language Processing Data Visualization Big Data Data Ingestion Data Munging Toolbox

22. Data Science  Data Exploration in R/Python  Uni, Bi & Multivariate Viz  ggplot2  Histogram & Pie (Uni)  Tree & Tree map  Scatter plot (Bi)  Line Charts (Bi) 50%

23. Data Science  Special Charts  Time line  Decision Tree  D3.js  Tableau  Matplotlib, vispy, bokeh, seaborn, pygal, folium, and networkx 50%

24. Data Science Fundamentals Statistics Programming Machine Learning Text Mining / Natural Language Processing Data Visualization Big Data Data Ingestion Data Munging Toolbox

25. Data Science  Map reduce Fundamentals  Hadoop Components  HDFS  Data replication principles  Name and data nodes  Using Mahout  Cassandra  MongoDB 70%

26. Data Science Fundamentals Statistics Programming Machine Learning Text Mining / Natural Language Processing Data Visualization Big Data Data Ingestion Data Munging Toolbox

27. Data Science  Data formats  Data discovery  Data sources  Data integration  Data fusion  Transformation  Data survey  Google OpenRefine 75%

28. Data Science Fundamentals Statistics Programming Machine Learning Text Mining / Natural Language Processing Data Visualization Big Data Data Ingestion Data Munging Toolbox

29. Data Science  Dimensionality Reduction  Normalization  Data scrubbing  Handling missing values  Denoising  Feature Extraction  Sampling  Principle Component analysis 80%

30. Data Science Fundamentals Statistics Programming Machine Learning Text Mining / Natural Language Processing Data Visualization Big Data Data Ingestion Data Munging Toolbox

31. Data Science  MS Excel  Python, R packages  Weka, Knime, RapidMiner  Hadoop, Spark, Storm  D3.js, ggplot2, Shiny, Matplotlib, Tableau  NLTK  WebScraper  scikit-learn, Theano, Keras  Cassandra, Mongo DB 100%

32. Data Science NumPy SciPy Matplotlib Pandas Scikit Learn Statsmodels Seaborn Scrapy Keras

33. Data Science facebook.com/mloey mohamedloey@gmail.com twitter.com/mloey linkedin.com/in/mloey mloey@fci.bu.edu.eg

Data science

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