With rise of Artificial Intelligence use of Data Science, Machine Learning (AI/ML) / Deep Learning (DL) in all areas of life, in particular to software and data handling/analysis, Silicon Interfaces and through its affiliate 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), model building(Tensorflow, sklearn) etc and Google Colab from Google Research to write and execute python code through browser.
- Data Analysis/Data Science:
- Import dataset(CSV, xls, JSON, etc), study, prepare, clean, and assess the needs to normalize the dataset, handle missing values, outlier detection, Etc.
- Plot Various graphs or visualizations to gain meaningful insights on the data.
- Partition Data for train data and test data.
- Machine Learning:
- Model multiple hidden neural network layers using statistical and probabilistic functions using ANN or use algorithms like decision trees, regressions, xbgboost Etc. from pandas and ML libraries, like TensorFlow function keras.
- The model can have various applications in fields of E-commerce, Semiconductors, Education, Finance, etc., and can be used for predictive or other such analysis.
- Deep Learning:
- Image Processing: Using CNNS for predictive analysis on images and training the model to learn the features, edges, and properties of the image along with object detection tasks.
- Natural language Processing: Using RNNs for simple NLP tasks such as Sentiment analysis , text generation Etc.
- Knowledge of GANS, Autoencoders, Time series analysis.
- Optimization:
- Study the effect of hyperparameters, optimizers (like adam), and activation functions (like "relu"), Loss function (MSE) and establish the learning rates (.001).
- Fine – Tuning Pre trained models used in image classification and Transformers.
- Goal:
- The model is applied to test data for actual versus predicted values which are plotted on heat maps showing almost 95% accuracy.
AI/ML
With rise of Artificial Intelligence use of Data Science, Machine Learning (AI/ML) / Deep Learning (DL) in all areas of life, in particular to software and data handling/analysis, Silicon Interfaces and through its affiliate 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), model building(Tensorflow, sklearn) etc and Google Colab from Google Research to write and execute python code through browser.
- Data Analysis/Data Science:
- Import dataset(CSV, xls, JSON, etc), study, prepare, clean, and assess the needs to normalize the dataset, handle missing values, outlier detection, Etc.
- Plot Various graphs or visualizations to gain meaningful insights on the data.
- Partition Data for train data and test data.
- Machine Learning:
- Model multiple hidden neural network layers using statistical and probabilistic functions using ANN or use algorithms like decision trees, regressions, xbgboost Etc. from pandas and ML libraries, like TensorFlow function keras.
- The model can have various applications in fields of E-commerce, Semiconductors, Education, Finance, etc., and can be used for predictive or other such analysis.
- Deep Learning:
- Image Processing: Using CNNS for predictive analysis on images and training the model to learn the features, edges, and properties of the image along with object detection tasks.
- Natural language Processing: Using RNNs for simple NLP tasks such as Sentiment analysis , text generation Etc.
- Knowledge of GANS, Autoencoders, Time series analysis.
- Optimization:
- Study the effect of hyperparameters, optimizers (like adam), and activation functions (like "relu"), Loss function (MSE) and establish the learning rates (.001).
- Fine – Tuning Pre trained models used in image classification and Transformers.
- Goal:
- The model is applied to test data for actual versus predicted values which are plotted on heat maps showing almost 95% accuracy.
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Environment Health and Safety.
