This introduction to the popular ggplot2 R graphics package will show you how to create a wide variety of graphical displays in R. Data sets and additional workshop materials available at http://projects.iq.harvard.edu/rtc/event/r-graphics
Visualization of multidimensional multi factorial big data is not large data, big data is complex data.We are trainnig decipher this complexcity data Visualization.
Data Visualization packages of R software lattice and ggplot 2.
Graphical Data-Mining Analysis With R Software
Learn the basics of data visualization in R. In this module, we explore the Graphics package and learn to build basic plots in R. In addition, learn to add title, axis labels and range. Modify the color, font and font size. Add text annotations and combine multiple plots. Finally, learn how to save the plots in different formats.
This introduction to the popular ggplot2 R graphics package will show you how to create a wide variety of graphical displays in R. Data sets and additional workshop materials available at http://projects.iq.harvard.edu/rtc/event/r-graphics
Visualization of multidimensional multi factorial big data is not large data, big data is complex data.We are trainnig decipher this complexcity data Visualization.
Data Visualization packages of R software lattice and ggplot 2.
Graphical Data-Mining Analysis With R Software
Learn the basics of data visualization in R. In this module, we explore the Graphics package and learn to build basic plots in R. In addition, learn to add title, axis labels and range. Modify the color, font and font size. Add text annotations and combine multiple plots. Finally, learn how to save the plots in different formats.
Implementing Generate-Test-and-Aggregate Algorithms on HadoopYu Liu
Generate-Test-and-Aggregate is a class of algorithms that can automatically derive efficient MapReduce programs.
MapReduce is a useful and popular programming model for large-scale parallel processing. However, for many complex problems, it is usually not easy to develop the efficient parallel algorithms that match MapReduce paradigm well.
The generator-based parallelization approach has been developed and introduced to simplify parallel programming by its automatic generating and optimizing mechanism. Efficient parallel algorithms can be generated from users' naive but correct programs by making use of generators which exploit knowledge of optimization theorems in the field of skeletal parallel programming. The obtained efficient-parallel algorithms are in the form that very fit for implementation with MapReduce.
By such an approach, a large class of generate-and-test-like computations can be efficiently programmed and computed over MapReduce. Thus a novel programming interface and framework can be built on top of MapReduce, and that would be helpful for resolving the difficulties on programmability and efficiency. In this paper we will introduce a framework that has such a novel programming interface for MapReduce. With this framework, users can just concentrate on making naive correct programs. We will show that a lot of so-called generate-and-test-like computations can be easily and efficiently implemented by this framework over MapReduce.
Data Mining Seminar - Graph Mining and Social Network Analysisvwchu
Delivered a formal presentation on course material for the Data Mining (EECS 4412) course at York University, Canada, about graph mining. Graphs have become increasingly important in modeling sophisticated structures and their interactions, with broad applications including chemical informatics, bioinformatics, computer vision, video indexing, text retrieval, and Web analysis. The formal seminar was 50 to 60 minutes followed by 10 to 20 minutes for questions.
https://wiki.eecs.yorku.ca/course_archive/2014-15/F/4412
https://wiki.eecs.yorku.ca/course_archive/2014-15/F/4412/lectures
OPTEX MATHEMATICAL MODELING AND MANAGEMENT SYSTEMJesus Velasquez
OPTEX MATHEMATICAL MODELING AND MANAGEMENT SYSTEM
is a META-FRAMEWORK for Mathematical Programming.
Oriented towards the design, implementation and setup of decision support systems based in mathematical programming with special emphasis in the development of final user apps:
- The algebraic formulation is independent from any programming language
- The models can be connected with any data server
Thereby generating apps using multiple commercial or noncommercial tech according to clients’ needs
Simple representations for learning: factorizations and similarities Gael Varoquaux
Real-life data seldom comes in the ideal form for statistical learning.
This talk focuses on high-dimensional problems for signals and
discrete entities: when dealing with many, correlated, signals or
entities, it is useful to extract representations that capture these
correlations.
Matrix factorization models provide simple but powerful representations. They are used for recommender systems across discrete entities such as users and products, or to learn good dictionaries to represent images. However they entail large computing costs on very high-dimensional data, databases with many products or high-resolution images. I will present an
algorithm to factorize huge matrices based on stochastic subsampling that gives up to 10-fold speed-ups [1].
With discrete entities, the explosion of dimensionality may be due to variations in how a smaller number of categories are represented. Such a problem of "dirty categories" is typical of uncurated data sources. I will discuss how encoding this data based on similarities recovers a useful category structure with no preprocessing. I will show how it interpolates between one-hot encoding and techniques used in character-level natural language processing.
[1] Stochastic subsampling for factorizing huge matrices, A Mensch, J Mairal, B Thirion, G Varoquaux, IEEE Transactions on Signal Processing 66 (1), 113-128
[2] Similarity encoding for learning with dirty categorical variables. P Cerda, G Varoquaux, B Kégl Machine Learning (2018): 1-18
FREQUENT SUBGRAPH MINING ALGORITHMS - A SURVEY AND FRAMEWORK FOR CLASSIFICATIONcscpconf
Data mining algorithms are facing the challenge to deal with an increasing number of complex
objects. Graph is a natural data structure used for modeling complex objects. Frequent subgraph
mining is another active research topic in data mining . A graph is a general model to represent
data and has been used in many domains like cheminformatics and bioinformatics. Mining
patterns from graph databases is challenging since graph related operations, such as subgraph
testing, generally have higher time complexity than the corresponding operations on itemsets,
sequences, and trees. Many frequent subgraph Mining algorithms have been proposed. SPIN,
SUBDUE, g_Span, FFSM, GREW are a few to mention. In this paper we present a detailed
survey on frequent subgraph mining algorithms, which are used for knowledge discovery in
complex objects and also propose a frame work for classification of these algorithms. The
purpose is to help user to apply the techniques in a task specific manner in various application domains and to pave wave for further research.
A Subgraph Pattern Search over Graph DatabasesIJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
Dual-time Modeling and Forecasting in Consumer Banking (2016)Aijun Zhang
Longitudinal and survival data are naturally observed with multiple origination dates. They form a dual-time data structure with horizontal axis representing the calendar time and the vertical axis representing the lifetime. In this talk we discuss how to model dual-time data based on a decomposition strategy and how to forecast over the time horizon. Various statistical techniques are used for treating fixed and random effects.
Among other fields, we share the potential applications in quantitative risk management, and demonstrate a large-scale credit risk analysis powered by big data computing.
LSGAN - SIMPle(Simple Idea Meaningful Performance Level up)Hansol Kang
LSGAN은 기존의 GAN loss가 아닌 MSE loss를 사용하여, 더욱 realistic한 데이터를 생성함.
LSGAN 논문 리뷰 및 PyTorch 기반의 구현.
[참고]
Mao, Xudong, et al. "Least squares generative adversarial networks." Proceedings of the IEEE International Conference on Computer Vision. 2017.
F. Petroni and L. Querzoni:
"GASGD: Stochastic Gradient Descent for Distributed Asynchronous Matrix Completion via Graph Partitioning."
In: Proceedings of the 8th ACM Conference on Recommender Systems (RecSys), 2014.
Abstract: "Matrix completion latent factors models are known to be an effective method to build recommender systems. Currently,
stochastic gradient descent (SGD) is considered one of the best latent factor-based algorithm for matrix completion. In this paper we discuss GASGD, a distributed asynchronous variant of SGD for large-scale matrix completion, that (i) leverages data partitioning schemes based on graph partitioning techniques, (ii) exploits specific characteristics of the input data and (iii) introduces an explicit parameter to tune synchronization frequency among the computing nodes. We empirically show how, thanks to these features, GASGD achieves a fast convergence rate incurring in smaller communication cost with respect to current asynchronous distributed SGD implementations."
Implementing Generate-Test-and-Aggregate Algorithms on HadoopYu Liu
Generate-Test-and-Aggregate is a class of algorithms that can automatically derive efficient MapReduce programs.
MapReduce is a useful and popular programming model for large-scale parallel processing. However, for many complex problems, it is usually not easy to develop the efficient parallel algorithms that match MapReduce paradigm well.
The generator-based parallelization approach has been developed and introduced to simplify parallel programming by its automatic generating and optimizing mechanism. Efficient parallel algorithms can be generated from users' naive but correct programs by making use of generators which exploit knowledge of optimization theorems in the field of skeletal parallel programming. The obtained efficient-parallel algorithms are in the form that very fit for implementation with MapReduce.
By such an approach, a large class of generate-and-test-like computations can be efficiently programmed and computed over MapReduce. Thus a novel programming interface and framework can be built on top of MapReduce, and that would be helpful for resolving the difficulties on programmability and efficiency. In this paper we will introduce a framework that has such a novel programming interface for MapReduce. With this framework, users can just concentrate on making naive correct programs. We will show that a lot of so-called generate-and-test-like computations can be easily and efficiently implemented by this framework over MapReduce.
Data Mining Seminar - Graph Mining and Social Network Analysisvwchu
Delivered a formal presentation on course material for the Data Mining (EECS 4412) course at York University, Canada, about graph mining. Graphs have become increasingly important in modeling sophisticated structures and their interactions, with broad applications including chemical informatics, bioinformatics, computer vision, video indexing, text retrieval, and Web analysis. The formal seminar was 50 to 60 minutes followed by 10 to 20 minutes for questions.
https://wiki.eecs.yorku.ca/course_archive/2014-15/F/4412
https://wiki.eecs.yorku.ca/course_archive/2014-15/F/4412/lectures
OPTEX MATHEMATICAL MODELING AND MANAGEMENT SYSTEMJesus Velasquez
OPTEX MATHEMATICAL MODELING AND MANAGEMENT SYSTEM
is a META-FRAMEWORK for Mathematical Programming.
Oriented towards the design, implementation and setup of decision support systems based in mathematical programming with special emphasis in the development of final user apps:
- The algebraic formulation is independent from any programming language
- The models can be connected with any data server
Thereby generating apps using multiple commercial or noncommercial tech according to clients’ needs
Simple representations for learning: factorizations and similarities Gael Varoquaux
Real-life data seldom comes in the ideal form for statistical learning.
This talk focuses on high-dimensional problems for signals and
discrete entities: when dealing with many, correlated, signals or
entities, it is useful to extract representations that capture these
correlations.
Matrix factorization models provide simple but powerful representations. They are used for recommender systems across discrete entities such as users and products, or to learn good dictionaries to represent images. However they entail large computing costs on very high-dimensional data, databases with many products or high-resolution images. I will present an
algorithm to factorize huge matrices based on stochastic subsampling that gives up to 10-fold speed-ups [1].
With discrete entities, the explosion of dimensionality may be due to variations in how a smaller number of categories are represented. Such a problem of "dirty categories" is typical of uncurated data sources. I will discuss how encoding this data based on similarities recovers a useful category structure with no preprocessing. I will show how it interpolates between one-hot encoding and techniques used in character-level natural language processing.
[1] Stochastic subsampling for factorizing huge matrices, A Mensch, J Mairal, B Thirion, G Varoquaux, IEEE Transactions on Signal Processing 66 (1), 113-128
[2] Similarity encoding for learning with dirty categorical variables. P Cerda, G Varoquaux, B Kégl Machine Learning (2018): 1-18
FREQUENT SUBGRAPH MINING ALGORITHMS - A SURVEY AND FRAMEWORK FOR CLASSIFICATIONcscpconf
Data mining algorithms are facing the challenge to deal with an increasing number of complex
objects. Graph is a natural data structure used for modeling complex objects. Frequent subgraph
mining is another active research topic in data mining . A graph is a general model to represent
data and has been used in many domains like cheminformatics and bioinformatics. Mining
patterns from graph databases is challenging since graph related operations, such as subgraph
testing, generally have higher time complexity than the corresponding operations on itemsets,
sequences, and trees. Many frequent subgraph Mining algorithms have been proposed. SPIN,
SUBDUE, g_Span, FFSM, GREW are a few to mention. In this paper we present a detailed
survey on frequent subgraph mining algorithms, which are used for knowledge discovery in
complex objects and also propose a frame work for classification of these algorithms. The
purpose is to help user to apply the techniques in a task specific manner in various application domains and to pave wave for further research.
A Subgraph Pattern Search over Graph DatabasesIJMER
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education.
International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
Dual-time Modeling and Forecasting in Consumer Banking (2016)Aijun Zhang
Longitudinal and survival data are naturally observed with multiple origination dates. They form a dual-time data structure with horizontal axis representing the calendar time and the vertical axis representing the lifetime. In this talk we discuss how to model dual-time data based on a decomposition strategy and how to forecast over the time horizon. Various statistical techniques are used for treating fixed and random effects.
Among other fields, we share the potential applications in quantitative risk management, and demonstrate a large-scale credit risk analysis powered by big data computing.
LSGAN - SIMPle(Simple Idea Meaningful Performance Level up)Hansol Kang
LSGAN은 기존의 GAN loss가 아닌 MSE loss를 사용하여, 더욱 realistic한 데이터를 생성함.
LSGAN 논문 리뷰 및 PyTorch 기반의 구현.
[참고]
Mao, Xudong, et al. "Least squares generative adversarial networks." Proceedings of the IEEE International Conference on Computer Vision. 2017.
F. Petroni and L. Querzoni:
"GASGD: Stochastic Gradient Descent for Distributed Asynchronous Matrix Completion via Graph Partitioning."
In: Proceedings of the 8th ACM Conference on Recommender Systems (RecSys), 2014.
Abstract: "Matrix completion latent factors models are known to be an effective method to build recommender systems. Currently,
stochastic gradient descent (SGD) is considered one of the best latent factor-based algorithm for matrix completion. In this paper we discuss GASGD, a distributed asynchronous variant of SGD for large-scale matrix completion, that (i) leverages data partitioning schemes based on graph partitioning techniques, (ii) exploits specific characteristics of the input data and (iii) introduces an explicit parameter to tune synchronization frequency among the computing nodes. We empirically show how, thanks to these features, GASGD achieves a fast convergence rate incurring in smaller communication cost with respect to current asynchronous distributed SGD implementations."
Correlations, Trends, and Outliers in ggplot2Chris Rucker
This project explains how ggplot2 can serve as an adequate instrument to visualize data; how in a fantastic world, a graph may construct its own identity outside of the rigid roles imposed upon itself by raw data.
r for data science 2. grammar of graphics (ggplot2) clean -refMin-hyung Kim
REFERENCES
#1. RStudio Official Documentations (Help & Cheat Sheet)
Free Webpage) https://www.rstudio.com/resources/cheatsheets/
#2. Wickham, H. and Grolemund, G., 2016.R for data science: import, tidy, transform, visualize, and model data. O'Reilly.
Free Webpage) https://r4ds.had.co.nz/
Cf) Tidyverse syntax (www.tidyverse.org), rather than R Base syntax
Cf) Hadley Wickham: Chief Scientist at RStudio. Adjunct Professor of Statistics at the University of Auckland, Stanford University, and Rice University
Data visualization using the grammar of graphicsRupak Roy
Well-documented data visualization using ggplot2, geom_density2d, stat_density_2d, geom_smooth, stat_ellipse, scatterplot and much more. Let me know if anything is required. Ping me at google #bobrupakroy
Exploratory data analysis is the process of quickly looking at data, formulating hypotheses, and testing those hypotheses. In practice, two of the most important components of this process are transforming data and visualizing it. This tutorial will be a hands-on, practical introduction to using R for data exploration, with an emphasis on data transformation and visualization. I will focus on using modern R packages like ggplot2, dplyr, and tidyr for this tutorial.
ggplot2: An Extensible Platform for Publication-quality GraphicsClaus Wilke
Talk given at the Symposium on Data Science and Statistics in Bellevue, Washington, May 29 - June 1, 2019, organized by the American Statistical Association and Interface Foundation of North America.
A survey of data visualization functions and packages in R. In particular, I discuss three approaches for data visualization in R: (i) the built-in base graphics functions, (ii) the ggplot2 package, and (iii) the lattice package. I also discuss some methods for visualizing large data sets.
Data visualization with multiple groups using ggplot2Rupak Roy
Well-documented visualization using geom_histogram(), facet(), geom_density(),
geom_boxplot(), geom_bin2d() and much more. Let me know if anything is required. Ping me @ google #bobrupakroy
SAT based planning for multiagent systemsRavi Kuril
Multi-agent Classical planning using SAT approach. This document describes the approach and discusses all the experiments and the respective results. I have considered State of the art tools for comparison purpose. Implementation code can be found on GitHub link https://github.com/ravikuril/SATbasedClassicalPlanning . For more Information contact me on ravikuril.du.or@gmail.com
R visualization: ggplot2, googlevis, plotly, igraph OverviewOlga Scrivner
In this workshop you will learn about 4 R packages to perform data visualization: ggplot2, googlevis, plotly and igraph. You will learn about their strengths and weaknesses. Code snippets are provides.
쉽게 설명하는 GAN (What is this? Gum? It's GAN.)Hansol Kang
Original GAN 논문 리뷰 및 PyTorch 기반의 구현.
딥러닝 개발환경 및 언어 비교.
[참고]
Goodfellow, Ian, et al. "Generative adversarial nets." Advances in neural information processing systems. 2014.
Wang, Su. "Generative Adversarial Networks (GAN) A Gentle Introduction."
초짜 대학원생의 입장에서 이해하는 Generative Adversarial Networks (https://jaejunyoo.blogspot.com/)
1시간만에 GAN(Generative Adversarial Network) 완전 정복하기 (https://www.slideshare.net/NaverEngineering/1-gangenerative-adversarial-network)
프레임워크 비교(https://deeplearning4j.org/kr/compare-dl4j-torch7-pylearn)
AI 개발에AI 개발에 가장 적합한 5가지 프로그래밍 언어 (http://www.itworld.co.kr/news/109189#csidxf9226c7578dd101b41d03bfedfec05e)
Git는 머꼬? GitHub는 또 머지?(https://www.slideshare.net/ianychoi/git-github-46020592)
svn 능력자를 위한 git 개념 가이드(https://www.slideshare.net/einsub/svn-git-17386752)
Loom & Functional Graphs in Clojure @ LambdaConf 2015Aysylu Greenberg
Graphs are ubiquitous data structures, and the algorithms for analyzing them are fascinating. Loom is an open-source Clojure library that provides many graph algorithms and visualizations. We will discuss how graphs are represented in a functional world, bridge the gap between procedural description of algorithms and their functional implementation, and learn about the way Loom integrates with other graph representations.
I am sharing the slides I used for teaching my "Data Science by R" class. You can sign up a class at http://www.nycdatascience.com/ ----NYC Data Science Academy. We offer classes in R, Python, Processing, D3.js, Hadoop, and etc.
- Why we need generics?
- Why Go doesn't have generics (yet)?
- Walk through Golang Generics Draft Design!
- Does Go1 has a type inference?
- Parameterized types
- Contracts vs Interfaces
Experience the thrill of Progressive Puzzle Adventures, like Scavenger Hunt Games and Escape Room Activities combined Solve Treasure Hunt Puzzles online.
Meet Dinah Mattingly – Larry Bird’s Partner in Life and Loveget joys
Get an intimate look at Dinah Mattingly’s life alongside NBA icon Larry Bird. From their humble beginnings to their life today, discover the love and partnership that have defined their relationship.
240529_Teleprotection Global Market Report 2024.pdfMadhura TBRC
The teleprotection market size has grown
exponentially in recent years. It will grow from
$21.92 billion in 2023 to $28.11 billion in 2024 at a
compound annual growth rate (CAGR) of 28.2%. The
teleprotection market size is expected to see
exponential growth in the next few years. It will grow
to $70.77 billion in 2028 at a compound annual
growth rate (CAGR) of 26.0%.
Panchayat Season 3 - Official Trailer.pdfSuleman Rana
The dearest series "Panchayat" is set to make a victorious return with its third season, and the fervor is discernible. The authority trailer, delivered on May 28, guarantees one more enamoring venture through the country heartland of India.
Jitendra Kumar keeps on sparkling as Abhishek Tripathi, the city-reared engineer who ends up functioning as the secretary of the Panchayat office in the curious town of Phulera. His nuanced depiction of a young fellow exploring the difficulties of country life while endeavoring to adjust to his new environmental factors has earned far and wide recognition.
Neena Gupta and Raghubir Yadav return as Manju Devi and Brij Bhushan Dubey, separately. Their dynamic science and immaculate acting rejuvenate the hardships of town administration. Gupta's depiction of the town Pradhan with an ever-evolving outlook, matched with Yadav's carefully prepared exhibition, adds profundity and credibility to the story.
New Difficulties and Experiences
The trailer indicates new difficulties anticipating the characters, as Abhishek keeps on wrestling with his part in the town and his yearnings for a superior future. The series has reliably offset humor with social editorial, and Season 3 looks ready to dig much more profound into the intricacies of rustic organization and self-awareness.
Watchers can hope to see a greater amount of the enchanting and particular residents who have become fan top picks. Their connections and the one of a kind cut of-life situations give a reviving and interesting portrayal of provincial India, featuring the two its appeal and its difficulties.
A Mix of Humor and Heart
One of the signs of "Panchayat" is its capacity to mix humor with sincere narrating. The trailer features minutes that guarantee to convey giggles, as well as scenes that pull at the heartstrings. This equilibrium has been a critical calculate the show's prosperity, resounding with crowds across different socioeconomics.
Creation Greatness
The creation quality remaining parts first rate, with the beautiful setting of Phulera town filling in as a scenery that upgrades the narrating. The meticulousness in portraying provincial life, joined with sharp composition and solid exhibitions, guarantees that "Panchayat" keeps on hanging out in the packed web series scene.
Expectation and Delivery
As the delivery date draws near, expectation for "Panchayat" Season 3 is at a record-breaking high. The authority trailer has previously created critical buzz, with fans enthusiastically anticipating the continuation of Abhishek Tripathi's excursion and the new undertakings that lie ahead in Phulera.
All in all, the authority trailer for "Panchayat" Season 3 recommends that watchers are in for another drawing in and engaging ride. Yet again with its charming characters, convincing story, and ideal mix of humor and show, the new season is set to enamor crowds. Write in your schedules and prepare to get back to the endearing universe of "Panchayat."
Meet Crazyjamjam - A TikTok Sensation | Blog EternalBlog Eternal
Crazyjamjam, the TikTok star everyone's talking about! Uncover her secrets to success, viral trends, and more in this exclusive feature on Blog Eternal.
Source: https://blogeternal.com/celebrity/crazyjamjam-leaks/
Young Tom Selleck: A Journey Through His Early Years and Rise to Stardomgreendigital
Introduction
When one thinks of Hollywood legends, Tom Selleck is a name that comes to mind. Known for his charming smile, rugged good looks. and the iconic mustache that has become synonymous with his persona. Tom Selleck has had a prolific career spanning decades. But, the journey of young Tom Selleck, from his early years to becoming a household name. is a story filled with determination, talent, and a touch of luck. This article delves into young Tom Selleck's life, background, early struggles. and pivotal moments that led to his rise in Hollywood.
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Early Life and Background
Family Roots and Childhood
Thomas William Selleck was born in Detroit, Michigan, on January 29, 1945. He was the second of four children in a close-knit family. His father, Robert Dean Selleck, was a real estate investor and executive. while his mother, Martha Selleck, was a homemaker. The Selleck family relocated to Sherman Oaks, California. when Tom was a child, setting the stage for his future in the entertainment industry.
Education and Early Interests
Growing up, young Tom Selleck was an active and athletic child. He attended Grant High School in Van Nuys, California. where he excelled in sports, particularly basketball. His tall and athletic build made him a standout player, and he earned a basketball scholarship to the University of Southern California (U.S.C.). While at U.S.C., Selleck studied business administration. but his interests shifted toward acting.
Discovery of Acting Passion
Tom Selleck's journey into acting was serendipitous. During his time at U.S.C., a drama coach encouraged him to try acting. This nudge led him to join the Hills Playhouse, where he began honing his craft. Transitioning from an aspiring athlete to an actor took time. but young Tom Selleck became drawn to the performance world.
Early Career Struggles
Breaking Into the Industry
The path to stardom was a challenging one for young Tom Selleck. Like many aspiring actors, he faced many rejections and struggled to find steady work. A series of minor roles and guest appearances on television shows marked his early career. In 1965, he debuted on the syndicated show "The Dating Game." which gave him some exposure but did not lead to immediate success.
The Commercial Breakthrough
During the late 1960s and early 1970s, Selleck began appearing in television commercials. His rugged good looks and charismatic presence made him a popular brand choice. He starred in advertisements for Pepsi-Cola, Revlon, and Close-Up toothpaste. These commercials provided financial stability and helped him gain visibility in the industry.
Struggling Actor in Hollywood
Despite his success in commercials. breaking into large acting roles remained a challenge for young Tom Selleck. He auditioned and took on small parts in T.V. shows and movies. Some of his early television appearances included roles in popular series like Lancer, The F.B.I., and Bracken's World. But, it would take a
As a film director, I have always been awestruck by the magic of animation. Animation, a medium once considered solely for the amusement of children, has undergone a significant transformation over the years. Its evolution from a rudimentary form of entertainment to a sophisticated form of storytelling has stirred my creativity and expanded my vision, offering limitless possibilities in the realm of cinematic storytelling.
Skeem Saam in June 2024 available on ForumIsaac More
Monday, June 3, 2024 - Episode 241: Sergeant Rathebe nabs a top scammer in Turfloop. Meikie is furious at her uncle's reaction to the truth about Ntswaki.
Tuesday, June 4, 2024 - Episode 242: Babeile uncovers the truth behind Rathebe’s latest actions. Leeto's announcement shocks his employees, and Ntswaki’s ordeal haunts her family.
Wednesday, June 5, 2024 - Episode 243: Rathebe blocks Babeile from investigating further. Melita warns Eunice to stay clear of Mr. Kgomo.
Thursday, June 6, 2024 - Episode 244: Tbose surrenders to the police while an intruder meddles in his affairs. Rathebe's secret mission faces a setback.
Friday, June 7, 2024 - Episode 245: Rathebe’s antics reach Kganyago. Tbose dodges a bullet, but a nightmare looms. Mr. Kgomo accuses Melita of witchcraft.
Monday, June 10, 2024 - Episode 246: Ntswaki struggles on her first day back at school. Babeile is stunned by Rathebe’s romance with Bullet Mabuza.
Tuesday, June 11, 2024 - Episode 247: An unexpected turn halts Rathebe’s investigation. The press discovers Mr. Kgomo’s affair with a young employee.
Wednesday, June 12, 2024 - Episode 248: Rathebe chases a criminal, resorting to gunfire. Turf High is rife with tension and transfer threats.
Thursday, June 13, 2024 - Episode 249: Rathebe traps Kganyago. John warns Toby to stop harassing Ntswaki.
Friday, June 14, 2024 - Episode 250: Babeile is cleared to investigate Rathebe. Melita gains Mr. Kgomo’s trust, and Jacobeth devises a financial solution.
Monday, June 17, 2024 - Episode 251: Rathebe feels the pressure as Babeile closes in. Mr. Kgomo and Eunice clash. Jacobeth risks her safety in pursuit of Kganyago.
Tuesday, June 18, 2024 - Episode 252: Bullet Mabuza retaliates against Jacobeth. Pitsi inadvertently reveals his parents’ plans. Nkosi is shocked by Khwezi’s decision on LJ’s future.
Wednesday, June 19, 2024 - Episode 253: Jacobeth is ensnared in deceit. Evelyn is stressed over Toby’s case, and Letetswe reveals shocking academic results.
Thursday, June 20, 2024 - Episode 254: Elizabeth learns Jacobeth is in Mpumalanga. Kganyago's past is exposed, and Lehasa discovers his son is in KZN.
Friday, June 21, 2024 - Episode 255: Elizabeth confirms Jacobeth’s dubious activities in Mpumalanga. Rathebe lies about her relationship with Bullet, and Jacobeth faces theft accusations.
Monday, June 24, 2024 - Episode 256: Rathebe spies on Kganyago. Lehasa plans to retrieve his son from KZN, fearing what awaits.
Tuesday, June 25, 2024 - Episode 257: MaNtuli fears for Kwaito’s safety in Mpumalanga. Mr. Kgomo and Melita reconcile.
Wednesday, June 26, 2024 - Episode 258: Kganyago makes a bold escape. Elizabeth receives a shocking message from Kwaito. Mrs. Khoza defends her husband against scam accusations.
Thursday, June 27, 2024 - Episode 259: Babeile's skillful arrest changes the game. Tbose and Kwaito face a hostage crisis.
Friday, June 28, 2024 - Episode 260: Two women face the reality of being scammed. Turf is rocked by breaking
Tom Selleck Net Worth: A Comprehensive Analysisgreendigital
Over several decades, Tom Selleck, a name synonymous with charisma. From his iconic role as Thomas Magnum in the television series "Magnum, P.I." to his enduring presence in "Blue Bloods," Selleck has captivated audiences with his versatility and charm. As a result, "Tom Selleck net worth" has become a topic of great interest among fans. and financial enthusiasts alike. This article delves deep into Tom Selleck's wealth, exploring his career, assets, endorsements. and business ventures that contribute to his impressive economic standing.
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Early Life and Career Beginnings
The Foundation of Tom Selleck's Wealth
Born on January 29, 1945, in Detroit, Michigan, Tom Selleck grew up in Sherman Oaks, California. His journey towards building a large net worth began with humble origins. , Selleck pursued a business administration degree at the University of Southern California (USC) on a basketball scholarship. But, his interest shifted towards acting. leading him to study at the Hills Playhouse under Milton Katselas.
Minor roles in television and films marked Selleck's early career. He appeared in commercials and took on small parts in T.V. series such as "The Dating Game" and "Lancer." These initial steps, although modest. laid the groundwork for his future success and the growth of Tom Selleck net worth. Breakthrough with "Magnum, P.I."
The Role that Defined Tom Selleck's Career
Tom Selleck's breakthrough came with the role of Thomas Magnum in the CBS television series "Magnum, P.I." (1980-1988). This role made him a household name and boosted his net worth. The series' popularity resulted in Selleck earning large salaries. leading to financial stability and increased recognition in Hollywood.
"Magnum P.I." garnered high ratings and critical acclaim during its run. Selleck's portrayal of the charming and resourceful private investigator resonated with audiences. making him one of the most beloved television actors of the 1980s. The success of "Magnum P.I." played a pivotal role in shaping Tom Selleck net worth, establishing him as a major star.
Film Career and Diversification
Expanding Tom Selleck's Financial Portfolio
While "Magnum, P.I." was a cornerstone of Selleck's career, he did not limit himself to television. He ventured into films, further enhancing Tom Selleck net worth. His filmography includes notable movies such as "Three Men and a Baby" (1987). which became the highest-grossing film of the year, and its sequel, "Three Men and a Little Lady" (1990). These box office successes contributed to his wealth.
Selleck's versatility allowed him to transition between genres. from comedies like "Mr. Baseball" (1992) to westerns such as "Quigley Down Under" (1990). This diversification showcased his acting range. and provided many income streams, reinforcing Tom Selleck net worth.
Television Resurgence with "Blue Bloods"
Sustaining Wealth through Consistent Success
In 2010, Tom Selleck began starring as Frank Reagan i
In the vast landscape of cinema, stories have been told, retold, and reimagined in countless ways. At the heart of this narrative evolution lies the concept of a "remake". A successful remake allows us to revisit cherished tales through a fresh lens, often reflecting a different era's perspective or harnessing the power of advanced technology. Yet, the question remains, what makes a remake successful? Today, we will delve deeper into this subject, identifying the key ingredients that contribute to the success of a remake.
Maximizing Your Streaming Experience with XCIPTV- Tips for 2024.pdfXtreame HDTV
In today’s digital age, streaming services have become an integral part of our entertainment lives. Among the myriad of options available, XCIPTV stands out as a premier choice for those seeking seamless, high-quality streaming. This comprehensive guide will delve into the features, benefits, and user experience of XCIPTV, illustrating why it is a top contender in the IPTV industry.
Create a Seamless Viewing Experience with Your Own Custom OTT Player.pdfGenny Knight
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From Slave to Scourge: The Existential Choice of Django Unchained. The Philos...Rodney Thomas Jr
#SSAPhilosophy #DjangoUnchained #DjangoFreeman #ExistentialPhilosophy #Freedom #Identity #Justice #Courage #Rebellion #Transformation
Welcome to SSA Philosophy, your ultimate destination for diving deep into the profound philosophies of iconic characters from video games, movies, and TV shows. In this episode, we explore the powerful journey and existential philosophy of Django Freeman from Quentin Tarantino’s masterful film, "Django Unchained," in our video titled, "From Slave to Scourge: The Existential Choice of Django Unchained. The Philosophy of Django Freeman!"
From Slave to Scourge: The Existential Choice of Django Unchained – The Philosophy of Django Freeman!
Join me as we delve into the existential philosophy of Django Freeman, uncovering the profound lessons and timeless wisdom his character offers. Through his story, we find inspiration in the power of choice, the quest for justice, and the courage to defy oppression. Django Freeman’s philosophy is a testament to the human spirit’s unyielding drive for freedom and justice.
Don’t forget to like, comment, and subscribe to SSA Philosophy for more in-depth explorations of the philosophies behind your favorite characters. Hit the notification bell to stay updated on our latest videos. Let’s discover the principles that shape these icons and the profound lessons they offer.
Django Freeman’s story is one of the most compelling narratives of transformation and empowerment in cinema. A former slave turned relentless bounty hunter, Django’s journey is not just a physical liberation but an existential quest for identity, justice, and retribution. This video delves into the core philosophical elements that define Django’s character and the profound choices he makes throughout his journey.
Link to video: https://youtu.be/GszqrXk38qk
Scandal! Teasers June 2024 on etv Forum.co.zaIsaac More
Monday, 3 June 2024
Episode 47
A friend is compelled to expose a manipulative scheme to prevent another from making a grave mistake. In a frantic bid to save Jojo, Phakamile agrees to a meeting that unbeknownst to her, will seal her fate.
Tuesday, 4 June 2024
Episode 48
A mother, with her son's best interests at heart, finds him unready to heed her advice. Motshabi finds herself in an unmanageable situation, sinking fast like in quicksand.
Wednesday, 5 June 2024
Episode 49
A woman fabricates a diabolical lie to cover up an indiscretion. Overwhelmed by guilt, she makes a spontaneous confession that could be devastating to another heart.
Thursday, 6 June 2024
Episode 50
Linda unwittingly discloses damning information. Nhlamulo and Vuvu try to guide their friend towards the right decision.
Friday, 7 June 2024
Episode 51
Jojo's life continues to spiral out of control. Dintle weaves a web of lies to conceal that she is not as successful as everyone believes.
Monday, 10 June 2024
Episode 52
A heated confrontation between lovers leads to a devastating admission of guilt. Dintle's desperation takes a new turn, leaving her with dwindling options.
Tuesday, 11 June 2024
Episode 53
Unable to resort to violence, Taps issues a verbal threat, leaving Mdala unsettled. A sister must explain her life choices to regain her brother's trust.
Wednesday, 12 June 2024
Episode 54
Winnie makes a very troubling discovery. Taps follows through on his threat, leaving a woman reeling. Layla, oblivious to the truth, offers an incentive.
Thursday, 13 June 2024
Episode 55
A nosy relative arrives just in time to thwart a man's fatal decision. Dintle manipulates Khanyi to tug at Mo's heartstrings and get what she wants.
Friday, 14 June 2024
Episode 56
Tlhogi is shocked by Mdala's reaction following the revelation of their indiscretion. Jojo is in disbelief when the punishment for his crime is revealed.
Monday, 17 June 2024
Episode 57
A woman reprimands another to stay in her lane, leading to a damning revelation. A man decides to leave his broken life behind.
Tuesday, 18 June 2024
Episode 58
Nhlamulo learns that due to his actions, his worst fears have come true. Caiphus' extravagant promises to suppliers get him into trouble with Ndu.
Wednesday, 19 June 2024
Episode 59
A woman manages to kill two birds with one stone. Business doom looms over Chillax. A sobering incident makes a woman realize how far she's fallen.
Thursday, 20 June 2024
Episode 60
Taps' offer to help Nhlamulo comes with hidden motives. Caiphus' new ideas for Chillax have MaHilda excited. A blast from the past recognizes Dintle, not for her newfound fame.
Friday, 21 June 2024
Episode 61
Taps is hungry for revenge and finds a rope to hang Mdala with. Chillax's new job opportunity elicits mixed reactions from the public. Roommates' initial meeting starts off on the wrong foot.
Monday, 24 June 2024
Episode 62
Taps seizes new information and recruits someone on the inside. Mary's new job
From the Editor's Desk: 115th Father's day Celebration - When we see Father's day in Hindu context, Nanda Baba is the most vivid figure which comes to the mind. Nanda Baba who was the foster father of Lord Krishna is known to provide love, care and affection to Lord Krishna and Balarama along with his wife Yashoda; Letter’s to the Editor: Mother's Day - Mother is a precious life for their children. Mother is life breath for her children. Mother's lap is the world happiness whose debt can never be paid.
3. Grammar of Graphics
• Framework for describing visualized data
– Mapping data onto a coordinate system
• Created by Leland Wilkinson
4.
5.
6.
7.
8. Your First ggplot2 Plot
> library(ggplot2)
> head(mpg)
manufacturer model displ year cyl trans drv cty hwy fl class
1 audi a4 1.8 1999 4 auto(l5) f 18 29 p compact
2 audi a4 1.8 1999 4 manual(m5) f 21 29 p compact
3 audi a4 2.0 2008 4 manual(m6) f 20 31 p compact
4 audi a4 2.0 2008 4 auto(av) f 21 30 p compact
5 audi a4 2.8 1999 6 auto(l5) f 16 26 p compact
6 audi a4 2.8 1999 6 manual(m5) f 18 26 p compact
9. Your First ggplot2 Plot
ggplot(data=mpg, aes(x=cty, y=hwy))
+ geom_point()
10. Your First ggplot2 Plot
The
data.frame
to plot
ggplot(data=mpg, aes(x=cty, y=hwy))
+ geom_point()
11. Your First ggplot2 Plot
The
data.frame Aesthetic
to plot Mappings
ggplot(data=mpg, aes(x=cty, y=hwy))
+ geom_point()
12. Your First ggplot2 Plot
The
data.frame Aesthetic
to plot Mappings
ggplot(data=mpg, aes(x=cty, y=hwy))
+ geom_point()
What geom
to use in
plotting
13. Your First ggplot2 Plot
library(ggplot2)
ggplot(data=mpg,
aes(x=cty, y=hwy))
+ geom_point()