Category: Machine Learning
Naveen PandeyGradient Descent for Linear Regression
Gradient Descent is defined as one of the most commonly used iterative optimization algorithm of machine learning to train the machine learning and deep learning models. It helps in finding the local minima of a function. The best way to define the local minima or local maxima of a function using gradient descent is as…
Read MoreNetflix Data Analysis Project using Python
Netflix is one of the most popular streaming services in the world, with a massive subscriber base. In this article we’re going to explore how data scientists can use Python to analyze Netflix data from various perspectives: how you watch Netflix and what you do once it finishes. As we have already worked with Jupyter…
Read MoreSpotify Data Analysis Project using Python
Data analysis is an important field in business, research and many other areas. Among the many uses of this data, there are helping to make decisions and publish research papers. The weather can also be predicted based on data analysis too. You’ll learn how to perform exploratory data analysis by analyzing musical-related data sets within…
Read MoreLinear Regression for Machine Learning
Linear regression is the statistical technique to find relationship between two or more variables. To predict the values of response (target) variable based on that values of predictors (external / independent variables) we can use linear regression. Simple linear regression is having only one external factor while Multiple liner regression is having more than one…
Read MoreWhat is GD, Batch GD, SGD, Mini-Batch GD?
What is Gradient Descent, Batch Gradient Descent, Stochastic Gradient Descent, Mini-Batch Gradient Descent? Gradient Descent This algorithm is a general algorithm that is used for optimization and for providing the optimal solution for various problems. It takes parameters in an iterative way and makes the cost function as simple as possible. 1) Define a cost…
Read MoreTop 40 Data Science Interview Questions and Answers
1 – What is F1 score? F1 score is a measure of the accuracy of a model. It is defined as the harmonic mean of precision and recall. F1 score is one of the most popular metrics for assessing how well a machine learning algorithm performs on predicting a target variable. F1 score ranges from…
Read MoreThe Future of AI & How It will Transform the World?
The future of AI technology is bright. It will affect our lives in many ways and it will change the way we live, work and play. The future is here, and it’s called artificial intelligence. Artificial intelligence is not just a passing fad or buzzword. It’s actually a revolutionary technology that will change the way…
Read MoreMachine Learning Interview questions Part -3
1 – Explain the difference between Variance and R squared error? Variance is a statistical measure of the dispersion of a distribution. It is often used in statistics to measure how much variation or “dispersion” there is from the mean. Variance can be calculated as the average squared deviation from the mean, which for a…
Read MoreImage processing using Machine Learning
We begin this chapter by examining a number of of the foremost image process algorithmic rule, then march on to machine learning implementation in image processing. The chapter at a look is as follows: Feature Mapping using the SIFT algorithmic rule Suppose we’ve 2 pictures. One image is of a bench in an exceedingly park.…
Read MoreMachine Learning Interview questions Part -2
1 – Define precision and recall? The precision and recall are two measures of data quality. They are used to determine the proportion of relevant data that is found by a search algorithm. Precision is a measure of how many of the retrieved records are correct. Recall is a measure of how many of the…
Read MoreMachine Learning Interview questions Part -1
1 – What are Different Types of Machine Learning algorithms? There are various types of machine learning algorithms. The most popular ones include supervised learning, unsupervised learning and reinforcement learning. Supervised Learning: Supervised machine learning is when a human has to provide the correct answer for the algorithm to learn from. This is done by…
Read MoreDifference between machine learning and machine reasoning?
Machine Learning is a subset of artificial intelligence, which is a type of statistical learning. It provides computer programs with the ability to automatically learn from data without being explicitly programmed where to look for patterns. Machine Learning algorithms do not need to be explicitly programmed where to look for patterns in order to find…
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Zero to Python Hero – Part 6/10: Functions and Modules in Python
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