Goals of ML Problem ?

The goal of any machine learning problem is to find a single model that will best predict our wanted outcome. Rather than making one model and hoping this model is the best/most accurate predictor we can make, ensemble methods take a myriad of models into account, and average those models to produce one final model. It is important to note that Decision Trees are not the only form of ensemble methods, just the most popular and relevant in DataScience today.

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Data Science Skills

Below are some of the data science skills that every data scientist must know: 1. Change is the only constant It’s not about “Learning Data Science”, it’s about “improving your Data Science skills! The subjects you are learning currently in Grad School are important because no learning go waste but, the real world practicality is totally different from the theory of the books which is taught for decades. Don’t cramp the information, rather understand the big picture. A report states that 50% of things that you learn today regarding IT will be outdated in 4 years. Technology can become obsolete but, learning can’t be. You should have the attitude of learning, updating your knowledge and focusing on your skills(Get your Basics clear) and not on the information you learn! This will help you to survive in this tough and competitive world (I am not scaring you, I am just asking you to prepare your best! You should start focusing on the below skills for becoming a data scientist –...

Data Science Interview Questions -Part 2

1) What are the differences between supervised and unsupervised learning? Supervised Learning Unsupervised Learning Uses known and labeled data as input Supervised learning has a feedback mechanism Most commonly used supervised learning algorithms are decision trees, logistic regression, and support vector machine Uses unlabeled data as input Unsupervised learning has no feedback mechanism Most commonly used unsupervised learning algorithms are k-means clustering, hierarchical clustering, and apriori algorithm 2) How is logistic regression done? Logistic regression measures the relationship between the dependent variable (our label of what we want to predict) and one or more independent variables (our features) by estimating probability using its underlying logistic function (sigmoid). The image shown below depicts how logistic regression works: The formula and graph for the sigmoid function is as shown: 3) Explain the steps in making a deci...

CondaValueError: Value error: invalid package specification

Recently I was trying to create Conda Environment and wanted to install Tensorflow but i have faced some issue , so i have done some research and done trouble shooting related to that . Here am going to share how to trouble shoot if you are getting Conda Value error while creating Conda environment and install tensorflow . Open Anaconda Prompt (as administrator if it was installed for all users) Run conda update conda Run the installer again Make sure all pkg are updated: Launch the console from Anaconda Navigator and conda create -n mypython python=3.6.8 After Installing Conda environment please active the conda now : conda activate mypython once conda environment has been activated kindly install tensorflow 2.0 by using this command pip install tensorflow==2.0.0 once Tensorflow has been successfully install kindly run the command : pip show tensorflow Try to Run Comman PIP Install Jupyter lab and after ins...

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