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Machine Learning Link: Awesome machine learning (Business needs…
Machine Learning
Link: Awesome machine learning
Data handling
Data division
train - test - validation
validation dataset
test dataset
training dataset
Cross-validation
Big data
Spark
Kafka
Hadoop
MapReduce
Google:
Cloud
Microsoft:
Azure
Data pre-processing
Principal Component Analysis (PCA)
Data cleansing
Outlier management
Missing values
Variable analysis
Data normalisation
Standardization
Post-Processing
Visualization
The beauty of data visualisation
example of visualizing statistics
Denormalization
Validation
Mathematics
Usage
Forward propagation
Overfitting
Regularisation
underfitting
classical statistics
Precision - Recall
False positives & false negatives
Accuracy
Business needs
Prediction
House price predictions
Clustering
Personalisation
Classification
Address matching
Fraud detection
Recommander Systems
Natural Language Processing (NLP)
Chatbots
examples
:star:
IBM: Watson
opportunities
anomaliedetectie
Models
Types
Supervised
Decision tree
Random forest
Support Vector Machine (SVM)
Neural Networks (NN)
https://www.youtube.com/watch?v=aircAruvnKk&=&feature=youtu.be
Neural Networks Demystified
Single layered NN
Deep NN
Convolutional NN
Deep learning
Perceptron
Recuring NN
Adverserial
k Nearest Neighbors
pros
high accuracy
no assumptions about data
cons
requires a lot of memory
computationally expensive
Rule-based learning
Unsupervised
Hierarchical clustering
K-means clustering
Reinforcement
Linear Regression
Simple Linear Regression
Logistic Regression
Libraries
Python
Tensorflow
scikit-learn
Java
DeepLearning4J :
Weka
Ethics
