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Neural Networks with Scikit-Learn and Python

Neural Networks with Scikit-Learn and Python

If you think that TensorFlow and PyTorch are the only ways to Neural Networks with Python then I would tell you that you are wrong. As there is another package to build Neural Networks with…

Binary Search Algorithm with Python

Binary Search Algorithm with Python

Here in this article, I will take you through how to implement a binary search algorithm with python. Binary search also called half-interval search, which is an algorithm used in computers systems to find the…

One Hot Encoding in Machine Learning

One Hot Encoding in Machine Learning

In machine learning, one hot encoding is a method of quantifying categorical data. Briefly, this method produces a vector of length equal to the number of categories in the dataset. In this article, I will…

Machine Learning books

Machine Learning Books

In this article, I’m going to introduce you to some of the best machine learning books that can help you understand machine learning concepts and guide you on your journey to becoming an expert in…

Daily Births Forecasting with Machine Learning

Daily Births Forecasting with Machine Learning

In this article, I will use the algorithm provided by Facebook, popularly known as Facebook Prophet Model. I will use the Facebook Prophet Model for Daily Births Forecasting using Machine Learning. The Data I will…

Data Science Resume

Data Science Resume

During my time in data science and machine learning, I have met many employers and interviewers. So here in this article, I would like to share how to prepare your data science resume and even…

Machine Learning Skills: Every Machine Learning Practitioner Should Know

Machine Learning Skills That You Need

If you are a machine learning practitioner and you have a good understanding of the complexities and know the benefits of leveraging machine learning to solve business problems. Now you should know that you need…

Use of Data Science

Use of Data Science

Imagine a big pile of data, what does that tell you? Data collections are expected to continue to grow day by day, as is the time to give once again. This leads to unsupervised data…

Linear Algebra for Machine Learning

Linear Algebra for Machine Learning

Linear algebra is one of the most important topics in machine learning. In this article, I will introduce you to the basic concepts of linear algebra for machine learning using NumPy. Why Linear Algebra for…

Machine Learning in Business Problems

Machine Learning in Business Problems

Machine learning in business problems finds its place in all aspects of IT, from social media to complex financial applications. Machine learning can be used to improve the customer experience, better manage and predict the…

Titanic Survival with Machine Learning

Titanic Survival with Machine Learning

In this article, I will take you through a very famous case study for machine learning practitioners which is to predict titanic survival with Machine Learning. I will first introduce you to this case study…

BERT in Machine Learning

BERT in Machine Learning

In this article, I’m going to take you through an in-depth review of BERT in Machine Learning for word embeddings produced by Google for Machine Learning. Here I’ll show you how to get started with…

Python Projects for Beginners

Python Projects for Beginners

If you have finished with most of the basics in Python and probably thinking about what’s next? Then it’s time to use your skills or analyse your skills by working on some python projects for…

Best IDE for Machine Learning

Best IDE for Machine Learning

IDEs are very important for running your code with a better experience. An Integrated Development Environment (IDE) generally consists of a code editor, a compiler or an interpreter, and a debugger which is accessible through…

data cleaning with python

Data Cleaning with Python

When analyzing and modelling data, a significant amount of time is spent preparing the data: loading, cleansing, transforming, and reorganizing. These tasks are often reported to take 80% or more of an analyst’s time. Sometimes…