Over the last few years I have explored, programmed, worked in, researched and taught Data Science / AI / ML / Analytics / Decision Science to multiple students and with many software professionals. I have collected many keywords that you can google and explore. This will help you to keep pace and learn about things happening is these areas. It’s like a glossary of words to search over internet. It’s a mix and match of technologies, algorithms, concepts, AI / ML / Information Technology terms, BigData words and so on in no particular order. I will keep expanding this till it’s a relatively exhaustive list.
- Automatic Machine Learning
- Transfer Learning
- Explainable Machine Learning
- Keras
- PyTorch
- MLR
- R
- Python
- Ggplot2
- MathplotLib
- MLib
- Spark
- Hadoop
- Tableau
- Chatbots
- Talend
- MongoDB
- Neo4j
- Kafka
- ELK
- NoSQL
- Cassandra
- AWS SageMaker
- SVM
- Decision Trees
- Regression: Logistic, Multiple, Simple Linear, Polynomial
- Scikit Learn
- KNIME
- BERT
- NLG
- NLP
- Random Forest
- Hyper parameters
- Boosting
- Association rules / mining – Apriori, FP-Growth
- Data mining
- OpenCV
- Self driving cars
- AI / Memory embedded SOCs, GPUs, TPUs
- Neural engine chipsets
- Neural Networks
- Deep Learning
- EDA
- Statistical & Algorithmic modelling
- Sampling
- Probability distributions
- Hypothesis testing
- Intervals, extrapolation, interpolation
- Scaling
- Normalization
- Agents, search, constraint satisfaction
- Rules based systems
- Semantic net
- Propositional logic
- Fuzzy reasoning
- Probabilistic learning
- First order logic
- Game theory
- Pipeline building
- Ludwig
- Bayesian belief networks
- Anaconda Navigator
- Jupyter
- Synthetic data
- Google dataset search
- Kaggle
- CNN / RNN / Feed forward / Back propagation / Multi-layer
- Tensorflow
- Deepfakes
- KNN
- K means clustering
- Naive Bayes
- Dimensionality reduction
- Feature engineering
- Supervised, unsupervised & reinforcement learning
- Markov model
- Time series
- Categorical & Continuous data
- Imputation
- Data analysis
- Classification / Clustering / Trees / Hyperplane
- Differential calculus
- Testing & training data
- Visualization
- Missing data treatment
- Scipy
- Pandas
- LightGBM
- Numpy
- Dplyr
- Google Collaboratory
- PyCharm
- Plotly
- Shiny
- Caret
- NLTK, Stanford NLP, OpenNLP
- Artificial intelligence
- SQL / PLSQL
- Data warehousing
- Cognitive computing
- Coral
- Arduino
- Raspberry Pi
- RTOS
- DARPA Spectrum Challenge
- 100 page ML book
- Equations, Functions, and Graphs
- Differentiation and Optimization
- Vectors and Matrices
- Statistics and Probability
- Operations management & research
- Unstructured, semi-structured & structured data
- Five Vs
- Descriptive, Predictive & Prescriptive analytics
- Model accuracy
- IoT / IIoT
- Recommendation Systems
- Real Time Analytics
- Google Analytics
If you are learning something by googling these topics, feel free to provide suggestions for adding more words here. You are welcome to discuss / suggest on top of this article as well. Thank you for reading.
Email me: Neil@TechAndTrain.com
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- www.TechAndTrain.com
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