Industry Ready Projects-Induction Session

Krish Naik · Advanced ·📐 ML Fundamentals ·5mo ago

Key Takeaways

Industry Ready AI projects induction session by Krish Naik covering machine learning fundamentals with live project and code walkthroughs

Original Description

Join our Industry Ready AI projects live sessions. The best part of our product is all the recordings of the projects is already available and we will be also be doing the project and code walk through in the live sessions so that you understand the project much better. We will be having the Live sessions every Saturday And Sunday. This is definitely my dream product which many people required to excel in industries. These projects are built completely from scratch with the Best frameworks and architectures. Happy Learning!!! Enroll and Be Industry Ready :https://www.krishnaik.in/projects
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Playlist

Uploads from Krish Naik · Krish Naik · 0 of 60

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1 Natural Language Processing|Stemming
Natural Language Processing|Stemming
Krish Naik
2 Natural Language Processing|BagofWords
Natural Language Processing|BagofWords
Krish Naik
3 Gaussian distribution or Normal Distribution in statisctics
Gaussian distribution or Normal Distribution in statisctics
Krish Naik
4 Natural Language Processing|TF-IDF for Machine Learning| Text Prerocessing
Natural Language Processing|TF-IDF for Machine Learning| Text Prerocessing
Krish Naik
5 Log Normal Distribution in Statistics
Log Normal Distribution in Statistics
Krish Naik
6 Covariance in Statistics
Covariance in Statistics
Krish Naik
7 Confusion matrix, Precision, Recall| Data Science Interview questions
Confusion matrix, Precision, Recall| Data Science Interview questions
Krish Naik
8 Tutorial 44-Balanced vs Imbalanced Dataset and how to handle Imbalanced Dataset
Tutorial 44-Balanced vs Imbalanced Dataset and how to handle Imbalanced Dataset
Krish Naik
9 Implementing a Spam classifier in python| Natural Language Processing
Implementing a Spam classifier in python| Natural Language Processing
Krish Naik
10 Tutorial 11-Exploratory Data Analysis(EDA) of Titanic dataset
Tutorial 11-Exploratory Data Analysis(EDA) of Titanic dataset
Krish Naik
11 Face Recognition using open CV and VGG 16 Transfer Learning
Face Recognition using open CV and VGG 16 Transfer Learning
Krish Naik
12 Pedestrian Detection using OpenCV from Videos
Pedestrian Detection using OpenCV from Videos
Krish Naik
13 Face and Eye Detection from Videos using HAAR Cascade Classifier
Face and Eye Detection from Videos using HAAR Cascade Classifier
Krish Naik
14 Reading, Writing and Displaying images with Opencv| OpenCV Tutorial
Reading, Writing and Displaying images with Opencv| OpenCV Tutorial
Krish Naik
15 OpenCV Installation | OpenCV tutorial
OpenCV Installation | OpenCV tutorial
Krish Naik
16 Face and Eye Detection from Images using HAAR Cascade Classifier
Face and Eye Detection from Images using HAAR Cascade Classifier
Krish Naik
17 Car Detection using HAAR Cascade and Opencv from Videos.
Car Detection using HAAR Cascade and Opencv from Videos.
Krish Naik
18 Using OpenFace for Face recognition in Keras
Using OpenFace for Face recognition in Keras
Krish Naik
19 OpenPose Tutorial with Tensorflow
OpenPose Tutorial with Tensorflow
Krish Naik
20 Multiple Linear Regression using python and sklearn
Multiple Linear Regression using python and sklearn
Krish Naik
21 Dimensional Reduction| Principal Component Analysis
Dimensional Reduction| Principal Component Analysis
Krish Naik
22 Movie Recommender System using Python
Movie Recommender System using Python
Krish Naik
23 TPR,FPR,FNR,TNR, Confusion Matrix
TPR,FPR,FNR,TNR, Confusion Matrix
Krish Naik
24 Precision, Recall and F1-Score
Precision, Recall and F1-Score
Krish Naik
25 Artificial Neural Network for Customer's Exit Prediction from Bank
Artificial Neural Network for Customer's Exit Prediction from Bank
Krish Naik
26 GridSearchCV- Select the best hyperparameter for any Classification Model
GridSearchCV- Select the best hyperparameter for any Classification Model
Krish Naik
27 RandomizedSearchCV- Select the best hyperparameter for any Classification Model
RandomizedSearchCV- Select the best hyperparameter for any Classification Model
Krish Naik
28 K Nearest Neighbor classification with Intuition and practical solution
K Nearest Neighbor classification with Intuition and practical solution
Krish Naik
29 K Means Clustering Intuition
K Means Clustering Intuition
Krish Naik
30 Create custom Alexa Skill- Lambda function- Part2
Create custom Alexa Skill- Lambda function- Part2
Krish Naik
31 Hierarchical Clustering intuition
Hierarchical Clustering intuition
Krish Naik
32 Implement Transfer Learning with a generic Code Template
Implement Transfer Learning with a generic Code Template
Krish Naik
33 Gender Classifier and Age Estimator using Resnet Convolution Neural Network
Gender Classifier and Age Estimator using Resnet Convolution Neural Network
Krish Naik
34 Unlock Your Application With Your Face using OpenCV
Unlock Your Application With Your Face using OpenCV
Krish Naik
35 Draw rectangle from webcam and sketch process it on a live feed
Draw rectangle from webcam and sketch process it on a live feed
Krish Naik
36 Complete Life Cycle of a Data Science Project
Complete Life Cycle of a Data Science Project
Krish Naik
37 How we can apply Machine Learning in Finance
How we can apply Machine Learning in Finance
Krish Naik
38 Deep Learning in Medical Science
Deep Learning in Medical Science
Krish Naik
39 How to switch your career to Data Science.
How to switch your career to Data Science.
Krish Naik
40 Linear Regression Mathematical Intuition
Linear Regression Mathematical Intuition
Krish Naik
41 Handle Categorical features using Python
Handle Categorical features using Python
Krish Naik
42 Machine Learning Algorithm- Which one to choose for your Problem?
Machine Learning Algorithm- Which one to choose for your Problem?
Krish Naik
43 DBSCAN Clustering Easily Explained with Implementation
DBSCAN Clustering Easily Explained with Implementation
Krish Naik
44 Curse of Dimensionality Easily explained| Machine Learning
Curse of Dimensionality Easily explained| Machine Learning
Krish Naik
45 Feature Selection Techniques Easily Explained | Machine Learning
Feature Selection Techniques Easily Explained | Machine Learning
Krish Naik
46 Tutorial 29-R square and Adjusted R square Clearly Explained| Machine Learning
Tutorial 29-R square and Adjusted R square Clearly Explained| Machine Learning
Krish Naik
47 Cross Validation using sklearn and python | Machine Learning
Cross Validation using sklearn and python | Machine Learning
Krish Naik
48 Handling Missing Data Easily Explained| Machine Learning
Handling Missing Data Easily Explained| Machine Learning
Krish Naik
49 Deploy Machine Learning Model using Flask
Deploy Machine Learning Model using Flask
Krish Naik
50 Deployment of Deep Learning Model using Flask
Deployment of Deep Learning Model using Flask
Krish Naik
51 How to Visualize Multiple Linear Regression in python
How to Visualize Multiple Linear Regression in python
Krish Naik
52 K Nearest Neighbour Easily Explained with Implementation
K Nearest Neighbour Easily Explained with Implementation
Krish Naik
53 Predicting Heart Disease using Machine Learning
Predicting Heart Disease using Machine Learning
Krish Naik
54 Predicting Lungs Disease using Deep Learning
Predicting Lungs Disease using Deep Learning
Krish Naik
55 Stock Sentiment Analysis using News Headlines
Stock Sentiment Analysis using News Headlines
Krish Naik
56 Random Forest(Bootstrap Aggregation) Easily Explained
Random Forest(Bootstrap Aggregation) Easily Explained
Krish Naik
57 Voting Classifier(Hard Voting and Soft Voting Classifier)
Voting Classifier(Hard Voting and Soft Voting Classifier)
Krish Naik
58 Credit Card Fraud Detection using Machine Learning from Kaggle
Credit Card Fraud Detection using Machine Learning from Kaggle
Krish Naik
59 Hyperparameter Optimization for Xgboost
Hyperparameter Optimization for Xgboost
Krish Naik
60 Tutorial 45-Handling imbalanced Dataset  using python- Part 1
Tutorial 45-Handling imbalanced Dataset using python- Part 1
Krish Naik

Join Krish Naik's Industry Ready AI projects live sessions to learn machine learning fundamentals and develop industry-ready AI solutions with live project and code walkthroughs. This session covers the best frameworks and architectures for building AI projects from scratch.

Key Takeaways
  1. Enroll in the Industry Ready AI projects course
  2. Join live sessions every Saturday and Sunday
  3. Participate in project and code walkthroughs
  4. Develop industry-ready AI solutions from scratch
  5. Apply machine learning fundamentals to real-world projects
💡 Building industry-ready AI solutions requires a strong foundation in machine learning fundamentals and the ability to apply them to real-world projects

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