With rise of Artificial Intelligence and Machine Learning (AI/ML) in all areas of life, in particular to Software and Data handling/analysis, infoWave is increasingly offering AI/ML services to alleviate the pains of analysing BIG Data.
We use Python language, and its repertoire of libraries for mathematical (NumPy), statistical (pandas), graph plotting (matplotlib/pyplot, seaborn), etc and Google Colab from Google Research to write and execute python code through browser.
- Import (csv), study, prepare, clean and assess the needs to normalize the dataset
- Model multiple hidden neural network layers using statistical and probabilistic functions from pandas and ML libraries, like TensorFlow function keras
- Partition Data for train data and train data
- model is fitted to train data,
- Study the effect of hyper parameters, optimizers (like adam), and activation functions (like "relu"), Loss function (MSE) and establish the learning rates (.001)
- The model is applied to test data for actual versus predicted values which are plotted on heat maps showing almost 95% accuracy.
The application of AI/ML Services has resulted in savings of time for the Financial, Retail and Semiconductor Industry
OS Support:
AI/ML
With rise of Artificial Intelligence and Machine Learning (AI/ML) in all areas of life, in particular to Software and Data handling/analysis, infoWave is increasingly offering AI/ML services to alleviate the pains of analysing BIG Data.
We use Python language, and its repertoire of libraries for mathematical (NumPy), statistical (pandas), graph plotting (matplotlib/pyplot, seaborn), etc and Google Colab from Google Research to write and execute python code through browser.
- Import (csv), study, prepare, clean and assess the needs to normalize the dataset
- Model multiple hidden neural network layers using statistical and probabilistic functions from pandas and ML libraries, like TensorFlow function keras
- Partition Data for train data and train data
- model is fitted to train data,
- Study the effect of hyper parameters, optimizers (like adam), and activation functions (like "relu"), Loss function (MSE) and establish the learning rates (.001)
- The model is applied to test data for actual versus predicted values which are plotted on heat maps showing almost 95% accuracy.
The application of AI/ML Services has resulted in savings of time for the Financial, Retail and Semiconductor Industry
OS Support:
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