1. Regression & Classification Linear Multivariate Linear Logistic Softmax Vectorization Gradient Calculation Stochastic Gradient Descent (SGD) Optimizers and Objectives 2. Regularization Ridge regression 3. Clustering k – Means EM Algorithms 4. Unsupervised Learning Autoencoders PCA Whitening sparse coding 5. Neural Network Perceptrons Backpropagation Restricted Boltzmann Machines Learning Vector Quantization 6. Deep Learning Stacked Autoencoders Convolution Neural Networks (Feature Extraction, Pooling)… Continue reading "11 Data Mining Algorithms"
To carry out an impactful Analysis you need a dataset of your choice in some scenario you need a dataset related to finance to carry out financial Analysis, in another scenario you need dataset related to words to carry out sentiment analysis or topic modelling, so there would be multiple scenarios. So the same situation keeps on repeating in the… Continue reading "Public Datasets for doing Data Analysis"
This post is for the folks who just started or about to start learning Data Science, As data science is a very wide field kindly plan your journey according to it. Start with one language, stick with it and try to understand the basic concepts that will lead you to a long way, I have assembled few resources especially for… Continue reading "Data Science Resources"