This webinar will be on 8th of May and on 12th of May. A neural network is a statistical technique that calculates weights for predictor characteristics by self-learning from data examples. Let's talk in more details.
Logistic regression is a statistical method for predicting binary classes. The outcome or target variable is dichotomous in nature. Dichotomous means there are only two possible classes. Let's talk in more details.
Intro to object detection using CV. Let's talk in more details.
The description of the data science project and the algorythm of work. Let's talk in more details.
Decision trees are supervised learning models used for problems involving classification and regression. Tree models present a high flexibility that comes at a price: on one hand, trees are able to capture complex non-linear relationships; on the other hand, they are prone to memorizing the noise present in a dataset. Let's talk in more details.
How to work with numpy array, the main functions of numpy. How to calculate integrals in SymPy. How to manipulate tabular data using pandas.
When it comes to explaining machine learning to those not concerned in the field, reinforcement learning is probably the easiest sub-field for this challenge. Let's talk in more details.
Your model is ready and now is the time to deploy it into productio. Here we will tell you how to do it, using Flask. Let's talk in more details.
Linear Regression is usually the first machine learning algorithm that every data scientist comes across. It is a simple model but everyone needs to master it as it lays the foundation for other machine learning algorithms. Let's talk in more details.
Pipeline can be used to chain multiple estimators into one. This is useful as there is often a fixed sequence of steps in processing the data, for example feature selection, normalization and classification. Let's talk in more details.
This webinar will be on 8th of May and on 12th of May. A neural network is a statistical technique that calculates weights for predictor characteristics by self-learning from data examples. Let's talk in more details.
Recommender systems aim to predict users’ interests and recommend product items that quite likely are interesting for them. They are among the most powerful machine learning systems that online retailers implement in order to drive sales. Let's talk in more details.
