Preview Data Analytics, Data Forecasting & Machine Learning Integrated Course

Recordings

Introduction

Installation Jupiter lab and setup, basic skills on python

Introduction to Python

Introduction to Python (followed by Project 2)

EDA using the Numpy library

EDA using the Pandas library

EDA using Matplotlib (Plotting graphs)

EDA using the Matplotlib

EDA using Seaborn Final Project

Final Project

Doubt Solving

Technical Interview Training

Introduction to Data Forecasting & Machine Learning

Inferential Statistics & Probability

Inferential Statistics & Probability (2)

Linear Regression and Probability Statistics

Linear Regression

Clustering k-means

Project 1 and Project 2 code walk through

Project 3 code walk through

Project 3 Code walk through and miscellaneous topics

Industry experience and doubts

Mock Interview

Power BI Dashboard Overview

SQL

Mock interview with doubts resolution

Interview Preparation and strategic planning

Miscellaneous topics

Classical ML Project

Are you sure you wanna do this ? 😛

Assessment

Study Material

_ GRU_Implementation_from_Scratch_01

_03- RNN_vs_GRU_Classification-01

Amazon Fine Food Reviews Analysis_Support Vector Machines

App PY-09

Boosting Learning - AdaBoost _ XGBoost

Chatbot

Cnn-01-01

FB_Prophet_tutorial-01

K means

LSTM

Main JS-13

mlp-01

NYC Taxi trip

padding_and_strides

Predicting species of iris data

Probability

Requirements Text

RNN_Classification-01

Statistics

Tutorial_time_series_analysis_and_forecasting

Util py-06

XG boost

Preview - Data Analytics, Data Forecasting & Machine Learning Integrated Course