Machine Learning part 7: random forests

#7 random forest Machine Learning 👉 ♡ supervised learning♡ unsupervised learning♡ reinforcement learning recap:🔖 types of supervised learning ✔ classification 📑 ✔ regression 📈 ✔ mixed ⚗– tree based – random forest 🎈– neural networks– support vector machines 🌳 overfitting and the problem with trees trees classify by drawing square boxes around the data, which… Continue Reading Machine Learning part 7: random forests

Machine Learning part 6: enthropy and gain

Machine Learning 👉 ♡ supervised learning ♡ unsupervised learning ♡ reinforcement learning recap: 🔖 types of supervised learning ✔ classification 📑 ✔ regression 📈 ✔ mixed ⚗ tree based :balloon: random forest neural networks support vector machines 🎗 enthropy enthropy is just another word for expected value in the past post, we decided what to… Continue Reading Machine Learning part 6: enthropy and gain

Machine Learning part 5: mixed methods

#5 mixed methods Machine Learning 👉 ♡ supervised learning♡ unsupervised learning♡ reinforcement learning types of supervised learning ✔ classification 🗒 ✔ regression 📈 ✔ mixed ⚗– tree based– random forest– neural networks– support vector machines mixed methods are used for classification and regression. 🌱 tree based method  those trees used for both for classification and… Continue Reading Machine Learning part 5: mixed methods

Machine Learning part 4: Gradient Descent and cost function

#4 gradient descent and cost function Machine Learning 👉 ♡ supervised learning♡ unsupervised learning♡ reinforced learning ☄ cost function cost function is also called mean squared error. well mean means sum of elements / number of elements. here we take the sum of all squared errors (error1 ^ 2 + error2 ^ 2 + error3… Continue Reading Machine Learning part 4: Gradient Descent and cost function

Plotting Hotspots in Mauritius with Python and Folium

Plotting Hotspots in Mauritius with Python and Folium

geo plotting has never been so easy. thanks dhrumil patel! download the data file here #Import Library import folium import pandas as pd #Load Data data = pd.read_csv(“hotspot.csv”) lat = data[‘Longitude’] lon = data[‘Latitude’] elevation = data[‘Location’] #Create base map map = folium.Map(location=[37.296933,-121.9574983], zoom_start = 5, tiles = “Mapbox bright”) #Plot Markers for lat, lon,… Continue Reading Plotting Hotspots in Mauritius with Python and Folium

Machine Learning part 3: regression

Machine Learning ♡ supervised learning♡ unsupervised learning♡ reinforcement learning #3 supervised learning: regression note: independent variables are also called *features* regression simply means prediction. there are many types of regression methods: – simple linear regression– multivariate linear regression– polynomial regression– ridge regression– lasso regression 🎁 simple linear regression means predicting for only two variables, a… Continue Reading Machine Learning part 3: regression

Machine Learning part 2: supervised learning

Machine Learning ♡ supervised learning♡ unsupervised learning♡ reinforcement learning #2 supervised learning in supervised learning we have labelled data available. the machine just see and do as we do. types of supervised learning ✅ classification 🔖 :– logistic regression– supervised clustering ✅ regression 📈 – linear regression (single value)– multivariate linear regression ✅ mixed ⚗–… Continue Reading Machine Learning part 2: supervised learning

Machine Learning part 1: introduction

Machine Learning part 1: introduction

what is it? wikipaedia defines machine learning as: _the scientific study of algorithms and statistical models that computer systems use to progressively improve their performance 📈 on a specific task. Machine learning algorithms build a mathematical model of sample data, known as “training data”, in order to make predictions or decisions without being explicitly programmed… Continue Reading Machine Learning part 1: introduction

Reviving Bertrand Russell Through Python

Reviving Bertrand Russell Through Python

famous authors are praised, respected, admired and missed due to their works. after reading all the titles of an excellent author, one is left wishing for more. curiously enough we now have the ability to produce more books that fit in the literary style, depth and topic tackling techniques of writers. perfection in this field… Continue Reading Reviving Bertrand Russell Through Python