Programming- AI, machine learning
Data science
R
- For statistical computing
- Stat modeling
- data analysis
- clustering time series forecasting
- OOP
Python,
it has a graph and stat packagees
- Matpotlib
- Numpy
- ScipPy
Deep Learning packages
- TensorFlow
- PyTorch
- Keras
SQL
- relational db
- NoSQL; non relational, distributed db
- MongoDB, Radis, Cassandra
Hadoop:
- Big data; management and storage of huge data
- It is a storage of Big Data
- Open source software
- It uses distributed storage system called Map Reduce
- PAckages in Hadoop: Pig, Hive, HBase
Tableau
- Data visualization software
- Specialized in graphical analysis if data
- Interactive visualisation and dashboards: treemaps, histograms, Box Plots
- It connects with spreadsheets, DB and cloud
Weko
- For getting familiar with ML in action
- Open source
- it was GUI (no code)
Other tools:
Power BI, Oracle, GIT, >_Shell, Scala, Apache Spark, Spreadsheets
Application of Data science
- Healthcare
- classification algorithms for detecting cancer and tumors
- it uses image recognition software
- analysis and and classification of patterns of genomic sequences in genetic ind.
- E-commerce
- recommandation sys based on historical purchase analysis
- ex: Amazon
- Manufacturing
- robots use reinforcement learning and image recognition
- Conversational agents
- using ML algorithms
- classify user queries
- provide appropriate reponse
- uses speech recon
- ex: Siri, Amazon
- Transport
- Reinforcement learning and detection algorithmsfor self driving cars
Machine learning
deep learn
- MATLAB for Deep Learning - MATLAB & Simulink
embedded sys
- Search Catalog | Stanford Online
AI
- Webots: robot simulator
- Robotics Toolbox | Peter Corke
- Downloads <?=@$title_suffix?>
- OpenRAVE | Welcome to Open Robotics Automation Virtual Environment | OpenRAVE Documentation
- Robotics simulator - Wikipedia
- STDR Simulator
- Autonomous Navigation for Flying Robots | edX
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