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Data mining
Basics
Softmax Functions
Accuracy Paradox
Forecasting Techniques
Softmax – Vec to Probability / One Hot (1-0 ) Encoding
Accuracy vs Training Size
Data Mining Data Types
Detect Model Overfitting With Training Accuracy ?
Deep Learning
LSTM Optimisation
LSTM Epoch Size Choice
LSTM Optimizer Choice ?
Learning Rate Choice : 1st Most Important Param
Detect Model Overfitting With Training Accuracy ?
Deep Learning and Brief History
TensorFlow
Deep Learning With TensorFlow
Understanding TensorFlow with 1 Image
Deep Learning Overfitting Prevention Strategy : Regularization
Deep Learning Overfitting Prevention / Space Reduction Strategy : Dropout
Learning Rate Choice : 1st Most Important Param
GD vs SGD vs Deep Learning Benchmark Comparision : Digit Recognition
Time Series
Cross Validation – Time Series Data
Time Series Data Features
Forecasting Techniques
PreProcess
PreProcessing : Dimensionality Reduction Why ?
Why Normalisation :Numerical Stability
Data Cleansing
Spark
Spark Optimization – II
Spark into Production Mode
Spark Tuning
Spark : Configuration + Tuning
Spark: Libraries : Sql + Streaming
Spark : Running Applications in cluster
Spark : Optimization (Application)
Spark: Transformations/ Actions
Spark Basics : RDD
Spark : Installation
Big Data
Hadoop : Name node Stuck at safenode
Symlink error while installing java on linux
Misc
Sw Engg
Software Design Pattern : Creation
Software Design Pattern : Structural
Software Design Pattern : Behavioral
S/W Enginering : BEST Programs -No, Good Enough – Yes
Docs
How To Create README : A Readable Markdown
README Best Practices + Sample
How to : Write Good Commits in GIT
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Data Science & Deep Learning
Tag:
data analysis
1 Post
Basics
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Data mining
Accuracy Paradox
April 15, 2015
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