Need a machine learning project
Budget: ₹12,500 – ₹37,500 INR
Machine Learning:
Machine learning technology needs a very crucial architectural designing and development. It begins with the very foundations like choice of libraries, dependencies, algorithms and their combinations.
Algorithms like
Linear regression
Logistic regression
Decision tree
SVM algorithm
Naive Bayes algorithm
KNN algorithm
K-means
Random forest algorithm
Dimensionality reduction algorithms
Gradient boosting algorithm and AdaBoosting algorithm
Libraries like
Tensor Flow
PyTorch
Apache Spark
Open CV
Fast Artificial Neural Networking
We use different combinations to achieve specific goals. Per say, we need to develop a face recognition system, for that first we need to understand how the system should work. So first we’ll choose how to recognise the face, so let us consider a few points. In a person’s face, there are many ways to differentiate one from another like eyebrows , eye color, skin tone and structure of the face. Hence we can use any of these factors to our usage, but the brow shape, eye color, skin tone may match with others, but structures of these variate from one person to another. So we can use this structuring to our benefit. We can use Object recognition to work with this, where using factors like point, edge and line recognition. So we now have a way to recognize. We need to build a database of faces as well for the program to learn from.
I want to go with an Artificial Neural Network to build this vibrant system. So there are three choices to go with
Convolutional Neural Networking
Recurrent Neural Networking
Deep Neural Network
And there are plenty of Algorithms to choose from within.
So this is how we achieve building Machine Learning systems. Hence the building of the ML starts with your vision and continues with our collaborative work where you and we work together at every step and build the bespoke ML you want.
Machine learning technology needs a very crucial architectural designing and development. It begins with the very foundations like choice of libraries, dependencies, algorithms and their combinations.
Algorithms like
Linear regression
Logistic regression
Decision tree
SVM algorithm
Naive Bayes algorithm
KNN algorithm
K-means
Random forest algorithm
Dimensionality reduction algorithms
Gradient boosting algorithm and AdaBoosting algorithm
Libraries like
Tensor Flow
PyTorch
Apache Spark
Open CV
Fast Artificial Neural Networking
We use different combinations to achieve specific goals. Per say, we need to develop a face recognition system, for that first we need to understand how the system should work. So first we’ll choose how to recognise the face, so let us consider a few points. In a person’s face, there are many ways to differentiate one from another like eyebrows , eye color, skin tone and structure of the face. Hence we can use any of these factors to our usage, but the brow shape, eye color, skin tone may match with others, but structures of these variate from one person to another. So we can use this structuring to our benefit. We can use Object recognition to work with this, where using factors like point, edge and line recognition. So we now have a way to recognize. We need to build a database of faces as well for the program to learn from.
I want to go with an Artificial Neural Network to build this vibrant system. So there are three choices to go with
Convolutional Neural Networking
Recurrent Neural Networking
Deep Neural Network
And there are plenty of Algorithms to choose from within.
So this is how we achieve building Machine Learning systems. Hence the building of the ML starts with your vision and continues with our collaborative work where you and we work together at every step and build the bespoke ML you want.