[FreeCourseSite.com] Udemy - Machine Learning Practical Workout 8 Real-World Projects

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Last Access Time	Dec. 23, 2024, 6:11 p.m.
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01 INTRODUCTION TO THE COURSE [QUICK WIN IN FIRST 10-12 MINS]/006 DL-and-ML-Practical-Tutorials-Package.zip 588.3 MB
05 PROJECT 3 PROPHET TIME SERIES - CHICAGO CRIME RATE/042 Data Vizualization.mp4 207.4 MB
07 PROJECT 5 LE-NET DEEP NETWORK - TRAFFIC SIGN CLASSIFICATION/056 Model Training.mp4 182.0 MB
10 PROJECT 8 USER-BASED COLLABORATIVE FILTERING - MOVIE RECOMMENDER SYSTEM/087 Collaborative Filter One Movie.mp4 169.2 MB
03 PROJECT 1 ARTIFICIAL NEURAL NETWORKS - CAR SALES PREDICTION/021 Data Visualization Cleaning.mp4 167.0 MB
10 PROJECT 8 USER-BASED COLLABORATIVE FILTERING - MOVIE RECOMMENDER SYSTEM/086 Visualize Dataset.mp4 157.1 MB
07 PROJECT 5 LE-NET DEEP NETWORK - TRAFFIC SIGN CLASSIFICATION/057 Model Evaluation.mp4 149.3 MB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/031 Data Vizualization.mp4 129.0 MB
01 INTRODUCTION TO THE COURSE [QUICK WIN IN FIRST 10-12 MINS]/004 ML vs. DL vs. AI.mp4 127.0 MB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/071 Visualize Dataset Part 1.mp4 124.6 MB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/027 Theory Part 2.mp4 124.0 MB
08 PROJECT 6 NATURAL LANGUAGE PROCESSING - E-MAIL SPAM FILTER/060 Naive Bayes Theory Part 2.mp4 120.8 MB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/076 Apply NLP to Data.mp4 112.5 MB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/081 Model Evaluation Part 2.mp4 112.1 MB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/037 Image Augmentation Part 1.mp4 109.5 MB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/038 Image augmentation Part 2.mp4 107.9 MB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/070 Load Dataset.mp4 107.4 MB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/035 Model Evaluation.mp4 105.6 MB
10 PROJECT 8 USER-BASED COLLABORATIVE FILTERING - MOVIE RECOMMENDER SYSTEM/085 Import Movie Dataset.mp4 102.5 MB
08 PROJECT 6 NATURAL LANGUAGE PROCESSING - E-MAIL SPAM FILTER/063 Count Vectorizer.mp4 102.3 MB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/033 Model Training Part 1.mp4 102.2 MB
03 PROJECT 1 ARTIFICIAL NEURAL NETWORKS - CAR SALES PREDICTION/022 Model Training 1.mp4 100.7 MB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/028 Theory Part 3.mp4 99.4 MB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/034 Model Training Part 2.mp4 90.7 MB
06 PROJECT 4 PROPHET TIME SERIES - AVOCADO MARKET/047 Explore Dataset.mp4 90.2 MB
01 INTRODUCTION TO THE COURSE [QUICK WIN IN FIRST 10-12 MINS]/005 ML Deep Dive.mp4 83.8 MB
07 PROJECT 5 LE-NET DEEP NETWORK - TRAFFIC SIGN CLASSIFICATION/055 Data Normalization.mp4 82.9 MB
10 PROJECT 8 USER-BASED COLLABORATIVE FILTERING - MOVIE RECOMMENDER SYSTEM/088 Full Movie Recomendation.mp4 82.8 MB
03 PROJECT 1 ARTIFICIAL NEURAL NETWORKS - CAR SALES PREDICTION/024 Model Evaluation.mp4 82.7 MB
02 ANACONDA AND JUPYTER INSTALLATION/012 How to run a Jupyter Notebook.mp4 82.1 MB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/029 Theory Part 4.mp4 79.9 MB
03 PROJECT 1 ARTIFICIAL NEURAL NETWORKS - CAR SALES PREDICTION/016 Theory Part 3.mp4 79.5 MB
03 PROJECT 1 ARTIFICIAL NEURAL NETWORKS - CAR SALES PREDICTION/014 Theory Part 1.mp4 77.8 MB
07 PROJECT 5 LE-NET DEEP NETWORK - TRAFFIC SIGN CLASSIFICATION/053 Load Data.mp4 76.3 MB
08 PROJECT 6 NATURAL LANGUAGE PROCESSING - E-MAIL SPAM FILTER/061 Spam Project Overview.mp4 75.9 MB
07 PROJECT 5 LE-NET DEEP NETWORK - TRAFFIC SIGN CLASSIFICATION/052 Project Overview.mp4 75.5 MB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/075 Exercise 3.mp4 73.5 MB
08 PROJECT 6 NATURAL LANGUAGE PROCESSING - E-MAIL SPAM FILTER/062 Visualize Dataset.mp4 73.2 MB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/074 Exercise 2.mp4 72.6 MB
05 PROJECT 3 PROPHET TIME SERIES - CHICAGO CRIME RATE/044 Make Predictions.mp4 71.6 MB
03 PROJECT 1 ARTIFICIAL NEURAL NETWORKS - CAR SALES PREDICTION/023 Model Training 2.mp4 71.4 MB
03 PROJECT 1 ARTIFICIAL NEURAL NETWORKS - CAR SALES PREDICTION/020 Import Data.mp4 70.9 MB
05 PROJECT 3 PROPHET TIME SERIES - CHICAGO CRIME RATE/040 Project Overview.mp4 70.9 MB
03 PROJECT 1 ARTIFICIAL NEURAL NETWORKS - CAR SALES PREDICTION/019 Project Overview.mp4 70.2 MB
06 PROJECT 4 PROPHET TIME SERIES - AVOCADO MARKET/046 Load Avocado Data.mp4 65.5 MB
06 PROJECT 4 PROPHET TIME SERIES - AVOCADO MARKET/048 Make Predictions Part 1.mp4 65.3 MB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/032 Data Preparation.mp4 60.9 MB
07 PROJECT 5 LE-NET DEEP NETWORK - TRAFFIC SIGN CLASSIFICATION/054 Data Exploration.mp4 59.5 MB
01 INTRODUCTION TO THE COURSE [QUICK WIN IN FIRST 10-12 MINS]/001 Welcome Message.mp4 59.2 MB
08 PROJECT 6 NATURAL LANGUAGE PROCESSING - E-MAIL SPAM FILTER/064 Model Training Part 1.mp4 56.4 MB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/030 Problem Statement.mp4 55.8 MB
05 PROJECT 3 PROPHET TIME SERIES - CHICAGO CRIME RATE/041 Import Dataset.mp4 55.7 MB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/073 Exercise 1.mp4 52.7 MB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/078 Model Training Part 1.mp4 50.1 MB
08 PROJECT 6 NATURAL LANGUAGE PROCESSING - E-MAIL SPAM FILTER/066 Testing.mp4 50.1 MB
03 PROJECT 1 ARTIFICIAL NEURAL NETWORKS - CAR SALES PREDICTION/015 Theory Part 2.mp4 49.2 MB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/026 Theory Part 1.mp4 45.9 MB
03 PROJECT 1 ARTIFICIAL NEURAL NETWORKS - CAR SALES PREDICTION/017 Theory Part 4.mp4 44.6 MB
06 PROJECT 4 PROPHET TIME SERIES - AVOCADO MARKET/050 Make Prediction Part 2.1.mp4 43.0 MB
01 INTRODUCTION TO THE COURSE [QUICK WIN IN FIRST 10-12 MINS]/003 Course overview.mp4 42.8 MB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/077 Apply Count Vectorizer to Data.mp4 40.0 MB
02 ANACONDA AND JUPYTER INSTALLATION/009 Download and Set up Anaconda.mp4 38.8 MB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/080 Model Evaluation Part 1.mp4 38.1 MB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/069 Project Overview.mp4 38.1 MB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/079 Model Training Part 2.mp4 37.8 MB
06 PROJECT 4 PROPHET TIME SERIES - AVOCADO MARKET/049 Make Predictions Part 2 (Region Specific).mp4 34.8 MB
08 PROJECT 6 NATURAL LANGUAGE PROCESSING - E-MAIL SPAM FILTER/065 Model Training Part 2.mp4 33.3 MB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/036 Save the Model.mp4 32.6 MB
07 PROJECT 5 LE-NET DEEP NETWORK - TRAFFIC SIGN CLASSIFICATION/051 Introduction.mp4 32.1 MB
03 PROJECT 1 ARTIFICIAL NEURAL NETWORKS - CAR SALES PREDICTION/018 Theory Part 5.mp4 31.2 MB
08 PROJECT 6 NATURAL LANGUAGE PROCESSING - E-MAIL SPAM FILTER/058 Introduction.mp4 29.8 MB
05 PROJECT 3 PROPHET TIME SERIES - CHICAGO CRIME RATE/043 Prepare the Data.mp4 28.7 MB
02 ANACONDA AND JUPYTER INSTALLATION/010 What is Jupyter Notebook.mp4 27.2 MB
03 PROJECT 1 ARTIFICIAL NEURAL NETWORKS - CAR SALES PREDICTION/013 Introduction.mp4 25.6 MB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/025 Introduction.mp4 25.1 MB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/068 Theory.mp4 24.7 MB
10 PROJECT 8 USER-BASED COLLABORATIVE FILTERING - MOVIE RECOMMENDER SYSTEM/084 Project Overview.mp4 23.2 MB
01 INTRODUCTION TO THE COURSE [QUICK WIN IN FIRST 10-12 MINS]/002 Updates on Udemy Reviews.mp4 23.1 MB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/067 Introduction.mp4 20.5 MB
05 PROJECT 3 PROPHET TIME SERIES - CHICAGO CRIME RATE/039 Introduction.mp4 20.4 MB
10 PROJECT 8 USER-BASED COLLABORATIVE FILTERING - MOVIE RECOMMENDER SYSTEM/082 Introduction.mp4 15.4 MB
06 PROJECT 4 PROPHET TIME SERIES - AVOCADO MARKET/045 Introduction.mp4 15.0 MB
05 PROJECT 3 PROPHET TIME SERIES - CHICAGO CRIME RATE/042 Data Vizualization.en.srt 41.0 KB
07 PROJECT 5 LE-NET DEEP NETWORK - TRAFFIC SIGN CLASSIFICATION/056 Model Training.en.srt 38.7 KB
10 PROJECT 8 USER-BASED COLLABORATIVE FILTERING - MOVIE RECOMMENDER SYSTEM/087 Collaborative Filter One Movie.en.srt 32.1 KB
10 PROJECT 8 USER-BASED COLLABORATIVE FILTERING - MOVIE RECOMMENDER SYSTEM/086 Visualize Dataset.en.srt 31.1 KB
03 PROJECT 1 ARTIFICIAL NEURAL NETWORKS - CAR SALES PREDICTION/021 Data Visualization Cleaning.en.srt 30.3 KB
07 PROJECT 5 LE-NET DEEP NETWORK - TRAFFIC SIGN CLASSIFICATION/057 Model Evaluation.en.srt 30.1 KB
03 PROJECT 1 ARTIFICIAL NEURAL NETWORKS - CAR SALES PREDICTION/022 Model Training 1.en.srt 27.4 KB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/027 Theory Part 2.en.srt 27.2 KB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/071 Visualize Dataset Part 1.en.srt 27.1 KB
08 PROJECT 6 NATURAL LANGUAGE PROCESSING - E-MAIL SPAM FILTER/059 Naive Bayes Theory Part 1.en.srt 26.2 KB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/033 Model Training Part 1.en.srt 25.5 KB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/029 Theory Part 4.en.srt 24.5 KB
01 INTRODUCTION TO THE COURSE [QUICK WIN IN FIRST 10-12 MINS]/004 ML vs. DL vs. AI.en.srt 24.5 KB
08 PROJECT 6 NATURAL LANGUAGE PROCESSING - E-MAIL SPAM FILTER/060 Naive Bayes Theory Part 2.en.srt 23.8 KB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/037 Image Augmentation Part 1.en.srt 23.0 KB
10 PROJECT 8 USER-BASED COLLABORATIVE FILTERING - MOVIE RECOMMENDER SYSTEM/085 Import Movie Dataset.en.srt 22.7 KB
08 PROJECT 6 NATURAL LANGUAGE PROCESSING - E-MAIL SPAM FILTER/063 Count Vectorizer.en.srt 21.7 KB
06 PROJECT 4 PROPHET TIME SERIES - AVOCADO MARKET/047 Explore Dataset.en.srt 21.5 KB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/070 Load Dataset.en.srt 21.3 KB
07 PROJECT 5 LE-NET DEEP NETWORK - TRAFFIC SIGN CLASSIFICATION/055 Data Normalization.en.srt 21.3 KB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/031 Data Vizualization.en.srt 21.2 KB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/076 Apply NLP to Data.en.srt 21.0 KB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/035 Model Evaluation.en.srt 20.9 KB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/028 Theory Part 3.en.srt 20.5 KB
01 INTRODUCTION TO THE COURSE [QUICK WIN IN FIRST 10-12 MINS]/005 ML Deep Dive.en.srt 20.4 KB
03 PROJECT 1 ARTIFICIAL NEURAL NETWORKS - CAR SALES PREDICTION/014 Theory Part 1.en.srt 19.6 KB
10 PROJECT 8 USER-BASED COLLABORATIVE FILTERING - MOVIE RECOMMENDER SYSTEM/088 Full Movie Recomendation.en.srt 19.1 KB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/034 Model Training Part 2.en.srt 18.6 KB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/081 Model Evaluation Part 2.en.srt 18.6 KB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/038 Image augmentation Part 2.en.srt 18.4 KB
07 PROJECT 5 LE-NET DEEP NETWORK - TRAFFIC SIGN CLASSIFICATION/053 Load Data.en.srt 18.2 KB
03 PROJECT 1 ARTIFICIAL NEURAL NETWORKS - CAR SALES PREDICTION/024 Model Evaluation.en.srt 18.2 KB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/075 Exercise 3.en.srt 16.7 KB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/074 Exercise 2.en.srt 16.5 KB
02 ANACONDA AND JUPYTER INSTALLATION/012 How to run a Jupyter Notebook.en.srt 16.4 KB
06 PROJECT 4 PROPHET TIME SERIES - AVOCADO MARKET/048 Make Predictions Part 1.en.srt 15.9 KB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/072 Visualize Dataset Part 2.en.srt 15.8 KB
03 PROJECT 1 ARTIFICIAL NEURAL NETWORKS - CAR SALES PREDICTION/016 Theory Part 3.en.srt 15.5 KB
08 PROJECT 6 NATURAL LANGUAGE PROCESSING - E-MAIL SPAM FILTER/062 Visualize Dataset.en.srt 15.3 KB
03 PROJECT 1 ARTIFICIAL NEURAL NETWORKS - CAR SALES PREDICTION/023 Model Training 2.en.srt 15.0 KB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/032 Data Preparation.en.srt 14.8 KB
08 PROJECT 6 NATURAL LANGUAGE PROCESSING - E-MAIL SPAM FILTER/061 Spam Project Overview.en.srt 14.8 KB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/073 Exercise 1.en.srt 14.7 KB
03 PROJECT 1 ARTIFICIAL NEURAL NETWORKS - CAR SALES PREDICTION/020 Import Data.en.srt 14.4 KB
08 PROJECT 6 NATURAL LANGUAGE PROCESSING - E-MAIL SPAM FILTER/064 Model Training Part 1.en.srt 13.9 KB
06 PROJECT 4 PROPHET TIME SERIES - AVOCADO MARKET/046 Load Avocado Data.en.srt 13.4 KB
07 PROJECT 5 LE-NET DEEP NETWORK - TRAFFIC SIGN CLASSIFICATION/052 Project Overview.en.srt 13.2 KB
10 PROJECT 8 USER-BASED COLLABORATIVE FILTERING - MOVIE RECOMMENDER SYSTEM/083 Theory.en.srt 13.2 KB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/030 Problem Statement.en.srt 12.7 KB
01 INTRODUCTION TO THE COURSE [QUICK WIN IN FIRST 10-12 MINS]/003 Course overview.en.srt 12.6 KB
05 PROJECT 3 PROPHET TIME SERIES - CHICAGO CRIME RATE/044 Make Predictions.en.srt 12.6 KB
07 PROJECT 5 LE-NET DEEP NETWORK - TRAFFIC SIGN CLASSIFICATION/054 Data Exploration.en.srt 12.3 KB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/078 Model Training Part 1.en.srt 11.9 KB
03 PROJECT 1 ARTIFICIAL NEURAL NETWORKS - CAR SALES PREDICTION/015 Theory Part 2.en.srt 11.1 KB
08 PROJECT 6 NATURAL LANGUAGE PROCESSING - E-MAIL SPAM FILTER/066 Testing.en.srt 10.9 KB
05 PROJECT 3 PROPHET TIME SERIES - CHICAGO CRIME RATE/041 Import Dataset.en.srt 10.8 KB
05 PROJECT 3 PROPHET TIME SERIES - CHICAGO CRIME RATE/040 Project Overview.en.srt 10.3 KB
03 PROJECT 1 ARTIFICIAL NEURAL NETWORKS - CAR SALES PREDICTION/017 Theory Part 4.en.srt 10.2 KB
03 PROJECT 1 ARTIFICIAL NEURAL NETWORKS - CAR SALES PREDICTION/019 Project Overview.en.srt 10.2 KB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/080 Model Evaluation Part 1.en.srt 9.5 KB
06 PROJECT 4 PROPHET TIME SERIES - AVOCADO MARKET/050 Make Prediction Part 2.1.en.srt 9.2 KB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/026 Theory Part 1.en.srt 8.7 KB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/069 Project Overview.en.srt 8.7 KB
06 PROJECT 4 PROPHET TIME SERIES - AVOCADO MARKET/049 Make Predictions Part 2 (Region Specific).en.srt 8.3 KB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/079 Model Training Part 2.en.srt 8.0 KB
03 PROJECT 1 ARTIFICIAL NEURAL NETWORKS - CAR SALES PREDICTION/018 Theory Part 5.en.srt 8.0 KB
08 PROJECT 6 NATURAL LANGUAGE PROCESSING - E-MAIL SPAM FILTER/065 Model Training Part 2.en.srt 7.2 KB
05 PROJECT 3 PROPHET TIME SERIES - CHICAGO CRIME RATE/043 Prepare the Data.en.srt 6.6 KB
02 ANACONDA AND JUPYTER INSTALLATION/009 Download and Set up Anaconda.en.srt 6.5 KB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/036 Save the Model.en.srt 6.4 KB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/077 Apply Count Vectorizer to Data.en.srt 6.4 KB
10 PROJECT 8 USER-BASED COLLABORATIVE FILTERING - MOVIE RECOMMENDER SYSTEM/084 Project Overview.en.srt 5.3 KB
02 ANACONDA AND JUPYTER INSTALLATION/010 What is Jupyter Notebook.en.srt 5.1 KB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/068 Theory.en.srt 4.7 KB
01 INTRODUCTION TO THE COURSE [QUICK WIN IN FIRST 10-12 MINS]/001 Welcome Message.en.srt 4.3 KB
01 INTRODUCTION TO THE COURSE [QUICK WIN IN FIRST 10-12 MINS]/008 BONUS 5 Benefits of Jupyter Notebook.html 2.9 KB
07 PROJECT 5 LE-NET DEEP NETWORK - TRAFFIC SIGN CLASSIFICATION/051 Introduction.en.srt 2.1 KB
11 Bonus Lectures/089 YOUR SPECIAL BONUS.html 2.0 KB
01 INTRODUCTION TO THE COURSE [QUICK WIN IN FIRST 10-12 MINS]/007 BONUS ML vs DL vs AI.html 1.9 KB
08 PROJECT 6 NATURAL LANGUAGE PROCESSING - E-MAIL SPAM FILTER/058 Introduction.en.srt 1.9 KB
01 INTRODUCTION TO THE COURSE [QUICK WIN IN FIRST 10-12 MINS]/002 Updates on Udemy Reviews.en.srt 1.7 KB
03 PROJECT 1 ARTIFICIAL NEURAL NETWORKS - CAR SALES PREDICTION/013 Introduction.en.srt 1.6 KB
04 PROJECT 2 DEEP NEURAL NETWORKS - CIFAR-10 CLASSIFICATION/025 Introduction.en.srt 1.5 KB
05 PROJECT 3 PROPHET TIME SERIES - CHICAGO CRIME RATE/039 Introduction.en.srt 1.4 KB
09 PROJECT 7 NATURAL LANGUAGE PROCESSING - YELP REVIEWS/067 Introduction.en.srt 1.4 KB
01 INTRODUCTION TO THE COURSE [QUICK WIN IN FIRST 10-12 MINS]/006 Download Course Materials.html 1.2 KB
10 PROJECT 8 USER-BASED COLLABORATIVE FILTERING - MOVIE RECOMMENDER SYSTEM/082 Introduction.en.srt 1.1 KB
02 ANACONDA AND JUPYTER INSTALLATION/011 Install Tensorflow.html 1.0 KB
06 PROJECT 4 PROPHET TIME SERIES - AVOCADO MARKET/045 Introduction.en.srt 1.0 KB
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