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What is Regularization in Machine Learning?
Regularization helps to solve the problem of overfitting in machine learning. How well a model fits training data determines how well it performs on unseen data. Poor performance can occur due to either overfitting or underfitting the data. Overfitting is a phenomenon...
How to Calculate Jaccard Similarity in Python
Understanding the similarity between two objects is a universal problem. In machine learning, you can use similarity measures for various issues. These include object detection, classification and segmentation tasks in computer vision and similarity between text...
Top 12 Python Libraries for Data Science and Machine Learning
Machine learning is the science of programming a computer to learn from different data and perform inference. Yesteryear, machine learning tasks involved manual coding all of the algorithms and mathematical and statistical formulae. Nowadays, we have fantastic...
The History of Reinforcement Learning
Reinforcement learning (RL) is an exciting and rapidly developing area of machine learning that significantly impacts the future of technology and our everyday lives. RL is a field separate from supervised and unsupervised learning focusing on solving problems through...
Introduction to Pandas: A Complete Tutorial for Beginners
Pandas is an open-source library providing high-performance, easy-to-use data structures, and data analysis tools for Python. It is one of the fundamental tools for data scientists and can be thought of like Python's Excel. With Pandas, you can work with many...
The Best Books For Machine Learning for Both Beginners and Experts
Machine learning (ML) is an exciting and rapidly expanding domain in Computer Science. ML is a field of study devoted to the automated improvement of computer algorithms through exposure to data. The knowledge base underneath ML consists of a broad range in topics in...
The History of Machine Learning
Machine learning is an exciting and rapidly developing field of study centered around the automated improvement (learning) of computer algorithms through experience with data. Through persistent innovation and research, the capabilities of machine learning are now in...
5 Significant Benefits of Online Learning for Data Science
The internet has made access to information very easy and affordable. Technology has been completely integrated into how we learn and how we work. From primary school all the way to degree level, it can all be supplemented or entirely provided by online education....
7 Best Tips to Help Get a Data Scientist Job From Scratch
You have developed a passion and now you want to embark on a new career, but you are unsure where to start to enter the space of data science. This post will provide you with clear, practical steps to get on the road to a rewarding and stimulating career path. The...
Paper Reading #2: XLNet Explained
One of the most celebrated, recent advancements in language understanding is the XLNet model from Carnegie Mellon University and Google. It takes the "best-of-both-worlds" approach by combining auto-encoding and autoregressive language modeling to achieve...
9 Best Tips For Early Career Research Focused Data Scientists
Embarking on a career in data science is an exciting challenge that requires a lot of initiative and a desire to learn and apply knowledge quickly. For research scientists, there is an emphasis on experimentation and scientific discovery. The methods and objectives...
How to Solve Python AttributeError: ‘numpy.float64’ object has no attribute ‘isna’
This error occurs if you try to call isna() on a numpy.float64 object. If you want to evaluate whether a value is NaN or not in a Series or DataFrame object, you use can use the Series.isna() and DataFrame.isna() methods respectively. For example, import pandas as pd...
How to Solve Python ModuleNotFoundError: no module named ‘webencodings’
A common error you may encounter when using Python is modulenotfounderror: no module named 'webencodings'. This error occurs if you do not install webencodings before importing it into your program or installing the library in the wrong environment. You can install...
How to Solve Python ModuleNotFoundError: No module named ‘google.auth’
A common error you may encounter when using Python is modulenotfounderror: no module named 'google.auth'. This error occurs if you do not install google-auth before importing it into your program or installing the library in the wrong environment. You can install...
How to Solve Python ModuleNotFoundError: no module named ‘mako’
A common error you may encounter when using Python is modulenotfounderror: no module named 'mako'. This error occurs if you do not install mako before importing it into your program or installing the library in the wrong environment. You can install mako in Python 3...
How to Solve Python ModuleNotFoundError: no module named ‘parso’
A common error you may encounter when using Python is modulenotfounderror: no module named 'parso'. This error occurs if you do not install parso before importing it into your program or installing the library in the wrong environment. You can install parso in Python...
How to Solve Python AttributeError: ‘_io.TextIOWrapper’ object has no attribute ‘replace’
This error occurs when you try to call the string method replace() on a File object. You can solve this error by reading the file to get a string and calling the replace() method on the file content. For example: with open('artists.txt', 'r') as f: content =...
Python How to Replace Negative Value with Zero in Pandas DataFrame
This tutorial will go three ways to replace negative values with zero in a Pandas DataFrame. This simplest way to do it is: # Import pandas module import pandas as pd # Create pandas DataFrame df = pd.DataFrame({"X": [4, 5, -3, 4, -5, 6], "Y": [3, -5, -6, 7, 3, -2],...
How to Solve Python Modulenotfounderror: no module named ‘Crypto.Cipher’
This error occurs when the Python interpreter cannot detect the Crypto.Cipher package in your current environment. You can solve this error by uninstalling crypto and pycrypto (if you have them installed) then install pycryptodome. For example, python3 -m pip...
How to Solve ValueError: Pandas data cast to numpy dtype of object. Check input data with np.asarray(data)
This error occurs when you try to fit a regression model to data but do not convert categorical variables to dummy variables before fitting. You can solve the error by using the pandas method get_dummies() to convert the categorical variable to dummy. For example,...
How to Solve Python ModuleNotFoundError: no module named ‘multidict’
A common error you may encounter when using Python is modulenotfounderror: no module named 'multidict'. This error occurs if you do not install multidict before importing it into your program or installing the library in the wrong environment. You can install...